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Erschienen in: Information Systems Frontiers 6/2020

25.06.2019 | Manuscript

RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers

verfasst von: Lawrence Bunnell, Kweku-Muata Osei-Bryson, Victoria Y. Yoon

Erschienen in: Information Systems Frontiers | Ausgabe 6/2020

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Abstract

Scholarly research has extensively examined a number of issues and challenges affecting recommender systems (e.g. ‘cold-start’, ‘scrutability’, ‘trust’, ‘context’, etc.). However, a comprehensive knowledge classification of the issues involved with recommender systems research has yet to be developed. A holistic knowledge representation of the issues affecting a domain is critical for research advancement. The aim of this study is to advance scholarly research within the domain of recommender systems through formal knowledge classification of issues and their relationships to one another within recommender systems research literature. In this study, we employ a rigorous ontology engineering process for development of a recommender system issues ontology. This ontology provides a formal specification of the issues affecting recommender systems research and development. The ontology answers such questions as, “What issues are associated with ‘trust’ in recommender systems research?”,What are issues associated with improving and evaluating the ‘performance’ of a recommender system?” or “What ‘contextual’ factors might a recommender systems developer wish to consider in order to improve the relevancy and usefulness of recommendations?” Additionally, as an intermediate representation step in the ontology acquisition process, a concept map of recommender systems issues has been developed to provide conceptual visualization of the issues so that researchers may discern broad themes as well as relationships between concepts. These knowledge representations may aid future researchers wishing to take an integrated approach to addressing the challenges and limitations associated with current recommender systems research.

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Literatur
Zurück zum Zitat Abass, A., Zhang, L., & Khan, S. (2015). A survey on context-aware recommender systems based on computational intelligence techniques. Computing, 97(7), 667–690. Abass, A., Zhang, L., & Khan, S. (2015). A survey on context-aware recommender systems based on computational intelligence techniques. Computing, 97(7), 667–690.
Zurück zum Zitat Adomavicius, G., Bockstedt, J., Curley, S., & Zhang, J. (2018). Effects of online recommendations on consumers’ willingness to pay. Information Systems Research, 29(1), 84–102. Adomavicius, G., Bockstedt, J., Curley, S., & Zhang, J. (2018). Effects of online recommendations on consumers’ willingness to pay. Information Systems Research, 29(1), 84–102.
Zurück zum Zitat Adomavicius, G., & Kwon, Y. O. (2011). Maximizing aggregate recommendation diversity: A graph-theoretic approach. In Proceedings of the 1st international workshop on novelty and diversity in recommender systems (pp. 3–10). Adomavicius, G., & Kwon, Y. O. (2011). Maximizing aggregate recommendation diversity: A graph-theoretic approach. In Proceedings of the 1st international workshop on novelty and diversity in recommender systems (pp. 3–10).
Zurück zum Zitat Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734–749. Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734–749.
Zurück zum Zitat Adomavicius, G., Tuzhilin, A. (2011). Context-aware recommender systems. In: Ricci F., Rokach L., Shapira B., Kantor P. (eds.) Recommender Systems Handbook (pp. 217-253). Springer, Boston, MA, Context-Aware Recommender Systems. Adomavicius, G., Tuzhilin, A. (2011). Context-aware recommender systems. In: Ricci F., Rokach L., Shapira B., Kantor P. (eds.) Recommender Systems Handbook (pp. 217-253). Springer, Boston, MA, Context-Aware Recommender Systems.
Zurück zum Zitat Aggarwal, C. (2016). Social and trust-centric recommendations. Recommender Systems the Textbook (pp. 345–384). Switzerland: Springer. Aggarwal, C. (2016). Social and trust-centric recommendations. Recommender Systems the Textbook (pp. 345–384). Switzerland: Springer.
Zurück zum Zitat Avery, C., & Zeckhauser, R. (1999). Recommender systems for evaluating computer messages. Communications of the ACM, 40(4), 88–89. Avery, C., & Zeckhauser, R. (1999). Recommender systems for evaluating computer messages. Communications of the ACM, 40(4), 88–89.
Zurück zum Zitat Balabanovic, M., & Shoham, Y. (1997). Fab: content-based, collaborative recommendation. Communications of the ACM, 40(3), 66–72. Balabanovic, M., & Shoham, Y. (1997). Fab: content-based, collaborative recommendation. Communications of the ACM, 40(3), 66–72.
Zurück zum Zitat Baker, C., & Cheung, K.-H. (2006). The evaluation of ontologies. In Semantic web: Revolutionizing knowledge discovery in the life sciences (pp. 139–158). New York: Springer Verlag. Baker, C., & Cheung, K.-H. (2006). The evaluation of ontologies. In Semantic web: Revolutionizing knowledge discovery in the life sciences (pp. 139–158). New York: Springer Verlag.
Zurück zum Zitat Bell, R.M., Koren, Y. (2007). Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights. In Proceedings: Seventh IEEE International Conference on Data Mining (pp. 43-52). Washington, DC: IEEE Computer Society. Bell, R.M., Koren, Y. (2007). Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights. In Proceedings: Seventh IEEE International Conference on Data Mining (pp. 43-52). Washington, DC: IEEE Computer Society.
Zurück zum Zitat Bera, P., Burton-Jones, A., & Wand, Y. (2014). Research note —How semantics and pragmatics interact in understanding conceptual models. Information Systems Research, 25(2), 401–419. Bera, P., Burton-Jones, A., & Wand, Y. (2014). Research note —How semantics and pragmatics interact in understanding conceptual models. Information Systems Research, 25(2), 401–419.
Zurück zum Zitat Beutel, A., Covington, P., Jain, S., Xu, C., Li, J. (2018). Latent cross: Making use of context in recurrent recommender systems. In Proceedings: 11th Annual International Conference on Web Search and Data Mining (pp. 46–54). Beutel, A., Covington, P., Jain, S., Xu, C., Li, J. (2018). Latent cross: Making use of context in recurrent recommender systems. In Proceedings: 11th Annual International Conference on Web Search and Data Mining (pp. 46–54).
Zurück zum Zitat Bobadilla, J., Ortega, F., Hernando, A., & Gutierrez, A. (2013). Recommender Systems Survey. Knowledge Based Systems, Vol., 46(C), 109–132. Bobadilla, J., Ortega, F., Hernando, A., & Gutierrez, A. (2013). Recommender Systems Survey. Knowledge Based Systems, Vol., 46(C), 109–132.
Zurück zum Zitat Bollen, D., Knijnenburg, B.P., Willemsen, M.C., Graus, M. (2010). Understanding choice overload in recommender systems. In: RecSys ‘10 proceedings of the fourth ACM conference on recommender systems (pp. 63–70). Bollen, D., Knijnenburg, B.P., Willemsen, M.C., Graus, M. (2010). Understanding choice overload in recommender systems. In: RecSys ‘10 proceedings of the fourth ACM conference on recommender systems (pp. 63–70).
Zurück zum Zitat Brank, J., Grobelnik, M., Mladenic, D. (2005). A survey of ontology evaluation techniques. In Proceedings of the conference on data mining and data warehouses (SiKDD). Brank, J., Grobelnik, M., Mladenic, D. (2005). A survey of ontology evaluation techniques. In Proceedings of the conference on data mining and data warehouses (SiKDD).
Zurück zum Zitat Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77–101. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77–101.
Zurück zum Zitat Bridge, D., Göker, M., & Smyth, B. (2005). Case-based recommender systems. The Knowledge Engineering Review, 20(3), 315–320. Bridge, D., Göker, M., & Smyth, B. (2005). Case-based recommender systems. The Knowledge Engineering Review, 20(3), 315–320.
Zurück zum Zitat Brynjolfsson, E., Hu, Y., & Smith, M. D. (2010). Long tails vs. Superstars: The effect of information technology on product variety and sales concentration patterns. Information Systems Research, 21(4), 736–747. Brynjolfsson, E., Hu, Y., & Smith, M. D. (2010). Long tails vs. Superstars: The effect of information technology on product variety and sales concentration patterns. Information Systems Research, 21(4), 736–747.
Zurück zum Zitat Brooke, J. (1996). SUS – A “quick and dirty” usability scale. In P. Jordan, B. Thomas, & B. Weerdmeester (Eds.), Usability evaluation in industry (pp. 189–194). London, UK: Taylor and Francis. Brooke, J. (1996). SUS – A “quick and dirty” usability scale. In P. Jordan, B. Thomas, & B. Weerdmeester (Eds.), Usability evaluation in industry (pp. 189–194). London, UK: Taylor and Francis.
Zurück zum Zitat Burgess, S., Sellitto, C., Cox, C., & Buultjens, J. (2011). Trust perceptions of online travel information by different content creators: Some social and legal implications. Information Systems Frontiers, 13(2), 221–235. Burgess, S., Sellitto, C., Cox, C., & Buultjens, J. (2011). Trust perceptions of online travel information by different content creators: Some social and legal implications. Information Systems Frontiers, 13(2), 221–235.
Zurück zum Zitat Burke, R. (1999). Integrating knowledge-based and collaborative-filtering recommender systems. In: Artificial Intelligence for Electronic Commerce: Papers from the AAAI Workshop (AAAI technical report WS-99-0 1, pp. 69–72). Burke, R. (1999). Integrating knowledge-based and collaborative-filtering recommender systems. In: Artificial Intelligence for Electronic Commerce: Papers from the AAAI Workshop (AAAI technical report WS-99-0 1, pp. 69–72).
Zurück zum Zitat Burke, R. (2002). Hybrid recommender systems: Surveys and experiments. User Modeling and User-Adapted Interaction, 12(4), 331–370. Burke, R. (2002). Hybrid recommender systems: Surveys and experiments. User Modeling and User-Adapted Interaction, 12(4), 331–370.
Zurück zum Zitat Burke, R., Mobasher, B., Williams, C., Bhaumik, R. (2006). Classification features for attack detection in collaborative recommender systems. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’06). New York: ACM. Burke, R., Mobasher, B., Williams, C., Bhaumik, R. (2006). Classification features for attack detection in collaborative recommender systems. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’06). New York: ACM.
Zurück zum Zitat Cacheda, F., Carneiro, V., Fernandez, D., and Formoso, V. (2011). Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems. ACM Transactions. Web 5, 1, Article 2, pp.1–3. https://doi.org/10.1145/1921591.1921593. Cacheda, F., Carneiro, V., Fernandez, D., and Formoso, V. (2011). Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems. ACM Transactions. Web 5, 1, Article 2, pp.1–3. https://​doi.​org/​10.​1145/​1921591.​1921593.
Zurück zum Zitat Campos, P. G., Diez, F., & Cantador, I. (2014). Time-aware recommender systems: A comprehensive survey and analysis of existing evaluation protocols. User Modeling and User-Adapted Interaction, 24(1–2), 67–119. Campos, P. G., Diez, F., & Cantador, I. (2014). Time-aware recommender systems: A comprehensive survey and analysis of existing evaluation protocols. User Modeling and User-Adapted Interaction, 24(1–2), 67–119.
Zurück zum Zitat Castagnos, S., Brun, A., Boyer, A., (2013). When diversity is needed…but not expected! In: Proceedings of the 3rd International Conference on Advances in Information Mining and Management (pp. 44–50). Castagnos, S., Brun, A., Boyer, A., (2013). When diversity is needed…but not expected! In: Proceedings of the 3rd International Conference on Advances in Information Mining and Management (pp. 44–50).
Zurück zum Zitat Castells, P., Vargas, S., Wang, J. (2011). Novelty and diversity metrics for recommender systems: Choice, discovery and relevance. International workshop on diversity in document retrieval at the ECIR 2011: The 33rd European conference on information retrieval, Dublin. Castells, P., Vargas, S., Wang, J. (2011). Novelty and diversity metrics for recommender systems: Choice, discovery and relevance. International workshop on diversity in document retrieval at the ECIR 2011: The 33rd European conference on information retrieval, Dublin.
Zurück zum Zitat Champiri, Z. D., Shahamiri, S. R., & Salim, S. S. B. (2015). A systematic review of scholar context-aware recommender systems. Expert Systems with Applications, 42, 1743–1758. Champiri, Z. D., Shahamiri, S. R., & Salim, S. S. B. (2015). A systematic review of scholar context-aware recommender systems. Expert Systems with Applications, 42, 1743–1758.
Zurück zum Zitat Chang, W.-L., & Jung, C.-F. (2017). A hybrid approach for personalized service staff recommendation. Information Systems Frontiers, 19(1), 149–163. Chang, W.-L., & Jung, C.-F. (2017). A hybrid approach for personalized service staff recommendation. Information Systems Frontiers, 19(1), 149–163.
Zurück zum Zitat Chen, N.-S., Kinshuk, Wei, C.-W., & Chen, H.-J. (2008). Mining e-learning domain concept map from academic articles. Computers and Education, 50(3), 1009–1021. Chen, N.-S., Kinshuk, Wei, C.-W., & Chen, H.-J. (2008). Mining e-learning domain concept map from academic articles. Computers and Education, 50(3), 1009–1021.
Zurück zum Zitat Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D., Sartin, M. (1999). Combining content-based and collaborative filters in an online newspaper. In: Proceedings of ACM SIGIR workshop on recommender systems. Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D., Sartin, M. (1999). Combining content-based and collaborative filters in an online newspaper. In: Proceedings of ACM SIGIR workshop on recommender systems.
Zurück zum Zitat Cremonesi, P., Koren, Y., & Turrin, R. (2010). Performance of recommender algorithms on top-n recommendation tasks. In Proceedings of the fourth ACM conference on recommender systems (pp. 39–46). Cremonesi, P., Koren, Y., & Turrin, R. (2010). Performance of recommender algorithms on top-n recommendation tasks. In Proceedings of the fourth ACM conference on recommender systems (pp. 39–46).
Zurück zum Zitat Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318–330. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318–330.
Zurück zum Zitat Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
Zurück zum Zitat Dyer, J. S., Fishburn, P. C., Steuer, R. E., Wallenius, J., & Zionts, S. (1992). Multiple Criteria decision making, multiattribute utility theory: the next ten years. Management Science, 38(5), 645–654. Dyer, J. S., Fishburn, P. C., Steuer, R. E., Wallenius, J., & Zionts, S. (1992). Multiple Criteria decision making, multiattribute utility theory: the next ten years. Management Science, 38(5), 645–654.
Zurück zum Zitat Felfernig, A., Burke, R. (2008). Constraint-based recommender systems: Technologies and research issues. In: ICEC ‘08 Proceedings of the 10th international conference on Electronic commerce, article no. 3. Felfernig, A., Burke, R. (2008). Constraint-based recommender systems: Technologies and research issues. In: ICEC ‘08 Proceedings of the 10th international conference on Electronic commerce, article no. 3.
Zurück zum Zitat Fernandez, M., Overbeeke, C., Sabou, M., & Motta, E. (2009). What makes a good ontology? A case-study in fine-grained knowledge reuse. In 4th Asian semantic web conference (ASWC 2009) (pp. 61–75). Shanghai, China. Fernandez, M., Overbeeke, C., Sabou, M., & Motta, E. (2009). What makes a good ontology? A case-study in fine-grained knowledge reuse. In 4th Asian semantic web conference (ASWC 2009) (pp. 61–75). Shanghai, China.
Zurück zum Zitat Ge, M., Delgado-Battenfeld, C., Jannach, D. (2010). Beyond accuracy: evaluating recommender systems by coverage and serendipity. In: Proceedings of the fourth ACM conference on Recommender systems (RecSys ’10). (257–260). New York: ACM. Ge, M., Delgado-Battenfeld, C., Jannach, D. (2010). Beyond accuracy: evaluating recommender systems by coverage and serendipity. In: Proceedings of the fourth ACM conference on Recommender systems (RecSys ’10). (257–260). New York: ACM.
Zurück zum Zitat Fernández-López, M. and Gómez-Pérez, A. and Juristo, N. (1997). Methontology: From Ontological Art Towards Ontological Engineering. In: AAAI-97 Spring Symposium Series, Stanford University, EEUU. Fernández-López, M. and Gómez-Pérez, A. and Juristo, N. (1997). Methontology: From Ontological Art Towards Ontological Engineering. In: AAAI-97 Spring Symposium Series, Stanford University, EEUU.
Zurück zum Zitat Goldberg, D., Nichols, D., Oki, B. M., & Terry, D. (1992). Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35(12), 61–70. Goldberg, D., Nichols, D., Oki, B. M., & Terry, D. (1992). Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35(12), 61–70.
Zurück zum Zitat Gomez-Perez, A. (1996). Towards a framework to verify knowledge sharing technology. Expert Systems with Applications, 11(4), 519–529. Gomez-Perez, A. (1996). Towards a framework to verify knowledge sharing technology. Expert Systems with Applications, 11(4), 519–529.
Zurück zum Zitat Gomez-Perez, A. (1999). Ontological engineering: A state of the art. Expert Updates: Knowledge Based Systems and. Applied Artificial Intelligence, 2(3), 33–43. Gomez-Perez, A. (1999). Ontological engineering: A state of the art. Expert Updates: Knowledge Based Systems and. Applied Artificial Intelligence, 2(3), 33–43.
Zurück zum Zitat Gómez-Pérez, A., Fernández-López, M., & Corcho, O. (2004). Ontological engineering: With examples from the areas of knowledge management, E-commerce and the semantic web. London: Springer. Gómez-Pérez, A., Fernández-López, M., & Corcho, O. (2004). Ontological engineering: With examples from the areas of knowledge management, E-commerce and the semantic web. London: Springer.
Zurück zum Zitat Gomez-Uribe, C., & Hunt, N. (2016). The Netflix recommender system: Algorithms, business value, and innovation. ACM Transactions on Management Information Systems (TMIS), 6(4), 1–19. Gomez-Uribe, C., & Hunt, N. (2016). The Netflix recommender system: Algorithms, business value, and innovation. ACM Transactions on Management Information Systems (TMIS), 6(4), 1–19.
Zurück zum Zitat Gretzel, U., & Fesenmaier, D. R. (2006). Persuasion in Recommender Systems. International Journal of Electronic Commerce, 11(2), 81–100. Gretzel, U., & Fesenmaier, D. R. (2006). Persuasion in Recommender Systems. International Journal of Electronic Commerce, 11(2), 81–100.
Zurück zum Zitat Gruber, T. R. (1995). Towards principles for the design of ontologies used for knowledge sharing? International Journal of Human-Computer Studies, 43(5–6), 907–928. Gruber, T. R. (1995). Towards principles for the design of ontologies used for knowledge sharing? International Journal of Human-Computer Studies, 43(5–6), 907–928.
Zurück zum Zitat Gruninger, M. and Fox, M.S. (1995). Methodology for the design and evaluation of ontologies. In: Proceedings of the workshop on basic ontological issues in knowledge sharing, IJCAI-95, Montreal. Gruninger, M. and Fox, M.S. (1995). Methodology for the design and evaluation of ontologies. In: Proceedings of the workshop on basic ontological issues in knowledge sharing, IJCAI-95, Montreal.
Zurück zum Zitat Hagel, J., & Singer, M. (1999). Net worth, shaping markets when customers make the rules. Boston: Harvard Business School Press. Hagel, J., & Singer, M. (1999). Net worth, shaping markets when customers make the rules. Boston: Harvard Business School Press.
Zurück zum Zitat Herlocker, J. L., Konstan, J. A., Borchers, A., & Riedl, J. (1999). An algorithmic framework for performing collaborative filtering. In SIGIR '99 proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval (pp. 230–237). Herlocker, J. L., Konstan, J. A., Borchers, A., & Riedl, J. (1999). An algorithmic framework for performing collaborative filtering. In SIGIR '99 proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval (pp. 230–237).
Zurück zum Zitat Herlocker, J. L., Konstan, J. A., & Riedl, J. (2000). Explaining collaborative filtering recommendations. In CSCW '00 proceedings of the 2000 ACM conference on computer supported cooperative work (pp. 241–250). Herlocker, J. L., Konstan, J. A., & Riedl, J. (2000). Explaining collaborative filtering recommendations. In CSCW '00 proceedings of the 2000 ACM conference on computer supported cooperative work (pp. 241–250).
Zurück zum Zitat Herlocker, J. L., Konstan, J. A., Terveen, L. G., & Riedl, J. T. (2004). Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems (TOIS), 22(1), 5–53. Herlocker, J. L., Konstan, J. A., Terveen, L. G., & Riedl, J. T. (2004). Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems (TOIS), 22(1), 5–53.
Zurück zum Zitat Hevner, A., March, S., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1), 75–105. Hevner, A., March, S., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1), 75–105.
Zurück zum Zitat Ho, Y.-C., Chiang, Y.-T., Hsu Yung-Jen, J. (2014). Who likes it more?: mining worth-recommending items from long tails by modeling relative preference. In: Proceedings of the 7th ACM international conference on Web search and data mining (pp. 253–262). New York: ACM Press. Ho, Y.-C., Chiang, Y.-T., Hsu Yung-Jen, J. (2014). Who likes it more?: mining worth-recommending items from long tails by modeling relative preference. In: Proceedings of the 7th ACM international conference on Web search and data mining (pp. 253–262). New York: ACM Press.
Zurück zum Zitat Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust online. Communications of the ACM, 42(4), 80–85. Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust online. Communications of the ACM, 42(4), 80–85.
Zurück zum Zitat Horridge, M., Mortensen, J.M., Parsia, B., Sattler, U., Musen, M.A. (2014). A study on the atomic decomposition of ontologies. Mika, P. et al. (Eds.) in proceedings: The Semantic Web – ISWC 2014: 13th International Semantic Web Conference (part II, LNCS 8797, pp. 65–80). Horridge, M., Mortensen, J.M., Parsia, B., Sattler, U., Musen, M.A. (2014). A study on the atomic decomposition of ontologies. Mika, P. et al. (Eds.) in proceedings: The Semantic Web – ISWC 2014: 13th International Semantic Web Conference (part II, LNCS 8797, pp. 65–80).
Zurück zum Zitat Hu, Y., Koren, Y. Volinsky, C. (2008). Collaborative filtering for implicit feedback datasets. 2008 Eighth IEEE Conference on Data Mining, Pisa (pp. 263–272). Hu, Y., Koren, Y. Volinsky, C. (2008). Collaborative filtering for implicit feedback datasets. 2008 Eighth IEEE Conference on Data Mining, Pisa (pp. 263–272).
Zurück zum Zitat Huang, S. (2011). Designing utility-based recommender systems for e-commerce: Evaluation of preference-elicitation methods. Electronic Commerce Research and Applications, 10(4), 398–407. Huang, S. (2011). Designing utility-based recommender systems for e-commerce: Evaluation of preference-elicitation methods. Electronic Commerce Research and Applications, 10(4), 398–407.
Zurück zum Zitat Isinkaye, F. O., Folajimi, Y. O., & Ojokoh, B. A. (2015). Recommendation systems: Principles, methods and evaluation. Egyptian Informatics Journal, 16(3), 261–273. Isinkaye, F. O., Folajimi, Y. O., & Ojokoh, B. A. (2015). Recommendation systems: Principles, methods and evaluation. Egyptian Informatics Journal, 16(3), 261–273.
Zurück zum Zitat Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995–1006. Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995–1006.
Zurück zum Zitat Jameson, A. (2004). More than the sum of its members: Challenges for group recommender systems. In: Working Conference on Advanced Visual Interfaces (48-54). New York: ACM. Jameson, A. (2004). More than the sum of its members: Challenges for group recommender systems. In: Working Conference on Advanced Visual Interfaces (48-54). New York: ACM.
Zurück zum Zitat Ji, A. T., Yeon, C., Kim, H. N., & Jo, G. S. (2007). Collaborative tagging in recommender systems. In M. A. Orgun & J. Thornton (Eds.), AI 2007: Advances in artificial intelligence. Lecture notes in computer science (4830). Berlin, Heidelberg: Springer. Ji, A. T., Yeon, C., Kim, H. N., & Jo, G. S. (2007). Collaborative tagging in recommender systems. In M. A. Orgun & J. Thornton (Eds.), AI 2007: Advances in artificial intelligence. Lecture notes in computer science (4830). Berlin, Heidelberg: Springer.
Zurück zum Zitat Jonassen, D.H., (2005). Tools for Representing Problems and the Knowledge Required to Solve Them, In: (eds) Tergan, Sigmar-Olaf ; Keller, Tanja. Knowledge and Information Visualization (LNCS 3426, pp. 82-94). Jonassen, D.H., (2005). Tools for Representing Problems and the Knowledge Required to Solve Them, In: (eds) Tergan, Sigmar-Olaf ; Keller, Tanja. Knowledge and Information Visualization (LNCS 3426, pp. 82-94).
Zurück zum Zitat KKR, Knowledge Representation and Reasoning Group (2018). HermiT OWL reasoner, information systems group, Department of Computer Science, University of Oxford. Retrieved on July 14, 2018 from http://www.hermit-reasoner.com/. Accessed 15 July 2018. KKR, Knowledge Representation and Reasoning Group (2018). HermiT OWL reasoner, information systems group, Department of Computer Science, University of Oxford. Retrieved on July 14, 2018 from http://​www.​hermit-reasoner.​com/​. Accessed 15 July 2018.
Zurück zum Zitat Kaminskas, M., & Bridge, D. (2017). Diversity, serendipity, novelty, and coverage: A survey and empirical analysis of beyond-accuracy objectives in recommender systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 7(1), 1–42. Kaminskas, M., & Bridge, D. (2017). Diversity, serendipity, novelty, and coverage: A survey and empirical analysis of beyond-accuracy objectives in recommender systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 7(1), 1–42.
Zurück zum Zitat Kazman, R., Abowd, G., Bass, L., Clemens, P. (1996). Scenario based analysis of software architecture, IEEE Software, November 1996. Kazman, R., Abowd, G., Bass, L., Clemens, P. (1996). Scenario based analysis of software architecture, IEEE Software, November 1996.
Zurück zum Zitat Kirakowski, J., & Corbett, M. (1993). SUMI: Software usability measurement inventory. British Journal of Educational Technology, 23(3), 210–214. Kirakowski, J., & Corbett, M. (1993). SUMI: Software usability measurement inventory. British Journal of Educational Technology, 23(3), 210–214.
Zurück zum Zitat Khan, M., Ibrahim, R., & Ghani, I. (2017). Cross domain recommender systems: A systematic literature review. ACM Computing Surveys (CSUR), 50(3), 1–34. Khan, M., Ibrahim, R., & Ghani, I. (2017). Cross domain recommender systems: A systematic literature review. ACM Computing Surveys (CSUR), 50(3), 1–34.
Zurück zum Zitat Kimble, C., de Vasconcelos, J. B., & Rocha, Á. (2016). Competence management in knowledge intensive organizations using consensual knowledge and ontologies. Information Systems Frontiers, 18(6), 1119–1130. Kimble, C., de Vasconcelos, J. B., & Rocha, Á. (2016). Competence management in knowledge intensive organizations using consensual knowledge and ontologies. Information Systems Frontiers, 18(6), 1119–1130.
Zurück zum Zitat Knijnenburg, B. P., Willemsen, M. C., Gantner, Z., Soncu, H., & Newell, C. (2012). Explaining the user experience of recommender systems. User Modeling and User-Adapted Interaction, 22(4–5), 441–504. Knijnenburg, B. P., Willemsen, M. C., Gantner, Z., Soncu, H., & Newell, C. (2012). Explaining the user experience of recommender systems. User Modeling and User-Adapted Interaction, 22(4–5), 441–504.
Zurück zum Zitat Komiak, S. Y. X., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly, 30(4), 941–960. Komiak, S. Y. X., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly, 30(4), 941–960.
Zurück zum Zitat Koprinska, I., Yasef, K. (2015) People-to-People Reciprocal Recommenders, Recommender Systems Handbook 2nd Edition, (eds. Ricci, F., Rokach, L., Shapira, B.) (pp. 545–567). Springer, U.S., Boston, MA. Koprinska, I., Yasef, K. (2015) People-to-People Reciprocal Recommenders, Recommender Systems Handbook 2nd Edition, (eds. Ricci, F., Rokach, L., Shapira, B.) (pp. 545–567). Springer, U.S., Boston, MA.
Zurück zum Zitat Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix factorization techniques for recommender systems. Computer, 42(8), 30–37. Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix factorization techniques for recommender systems. Computer, 42(8), 30–37.
Zurück zum Zitat Koutrika, G., Bercovitz, B., Garcia, H. (2009). FlexRecs: expressing and combining flexible recommendations. In: Proceedings of the 35th SIGMOD International Conference on Management of Data (pp. 745–757). Providence: ACM. Koutrika, G., Bercovitz, B., Garcia, H. (2009). FlexRecs: expressing and combining flexible recommendations. In: Proceedings of the 35th SIGMOD International Conference on Management of Data (pp. 745–757). Providence: ACM.
Zurück zum Zitat Kretzer, M., & Maedche, A. (2018). Designing social nudges for enterprise recommendation agents: An investigation in the business intelligence systems context. Journal of the Association for Information Systems, 19(12), 1145–1186. Kretzer, M., & Maedche, A. (2018). Designing social nudges for enterprise recommendation agents: An investigation in the business intelligence systems context. Journal of the Association for Information Systems, 19(12), 1145–1186.
Zurück zum Zitat Krulwich, B. (1997). Lifestyle Finder: Intelligent User Profiling Using Large-Scale Demographic Data. Artificial Intelligence Magazine, 18(2), 37–45. Krulwich, B. (1997). Lifestyle Finder: Intelligent User Profiling Using Large-Scale Demographic Data. Artificial Intelligence Magazine, 18(2), 37–45.
Zurück zum Zitat Lam, S.K., Frankowski, D., Riedl, J. (2006). Do you trust your recommendations? An exploration of security and privacy issues in recommender systems. In: Müller G. (eds) Emerging Trends in Information and Communication Security. Lecture Notes in Computer Science (3995. pp. 12–29). Springer, Berlin, Heidelberg. Lam, S.K., Frankowski, D., Riedl, J. (2006). Do you trust your recommendations? An exploration of security and privacy issues in recommender systems. In: Müller G. (eds) Emerging Trends in Information and Communication Security. Lecture Notes in Computer Science (3995. pp. 12–29). Springer, Berlin, Heidelberg.
Zurück zum Zitat Lamb, R., & Kling, R. (2003). Reconceptualizing users as social actors in information systems research. MIS Quarterly, 27(2), 197–235. Lamb, R., & Kling, R. (2003). Reconceptualizing users as social actors in information systems research. MIS Quarterly, 27(2), 197–235.
Zurück zum Zitat Lee, A. S., & Hubona, G. S. (2009). A scientific basis for rigor in information systems. MIS Quarterly, 33(2), 237–262. Lee, A. S., & Hubona, G. S. (2009). A scientific basis for rigor in information systems. MIS Quarterly, 33(2), 237–262.
Zurück zum Zitat Levandoski, J.J., Sarwat, M., Eldawy, A., Mokbel, M.F. (2012). Lars: A location-aware recommender system. In Proceedings: IEEE 28th International Conference on Data Engineering (450–461). Washington, DC: IEEE. Levandoski, J.J., Sarwat, M., Eldawy, A., Mokbel, M.F. (2012). Lars: A location-aware recommender system. In Proceedings: IEEE 28th International Conference on Data Engineering (450–461). Washington, DC: IEEE.
Zurück zum Zitat Li, B., Yang, Q., & Xue, X. (2009). Transfer learning for collaborative filtering via a rating-matrix generative model. In ICML '09 proceedings of the 26th annual international conference on machine learning (pp. 617–624). Li, B., Yang, Q., & Xue, X. (2009). Transfer learning for collaborative filtering via a rating-matrix generative model. In ICML '09 proceedings of the 26th annual international conference on machine learning (pp. 617–624).
Zurück zum Zitat Li, T., & Unger, T. (2012). Willing to pay for quality personalization? Trade-off between quality and privacy. European Journal of Information Systems, 21(6), 621–642. Li, T., & Unger, T. (2012). Willing to pay for quality personalization? Trade-off between quality and privacy. European Journal of Information Systems, 21(6), 621–642.
Zurück zum Zitat Li, Y., Thomas, M. A., & Osei-Bryson, K. M. (2017). Ontology-based data mining model management for self-service knowledge discovery. Information Systems Frontiers, 19(4), 925–943. Li, Y., Thomas, M. A., & Osei-Bryson, K. M. (2017). Ontology-based data mining model management for self-service knowledge discovery. Information Systems Frontiers, 19(4), 925–943.
Zurück zum Zitat Linden, G., Smith, B., York, J. (2003). Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing, Vol. 7(1), pp. 76–80. Linden, G., Smith, B., York, J. (2003). Amazon.​com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing, Vol. 7(1), pp. 76–80.
Zurück zum Zitat Lorenzi, F., & Ricci, F. (2003). Case-based recommender systems: A unifying view. In B. Mobasher & S. S. Anand (Eds.), Intelligent techniques for web personalization. Lecture notes in computer science (Vol. 3169). Berlin, Heidelberg: Springer. Lorenzi, F., & Ricci, F. (2003). Case-based recommender systems: A unifying view. In B. Mobasher & S. S. Anand (Eds.), Intelligent techniques for web personalization. Lecture notes in computer science (Vol. 3169). Berlin, Heidelberg: Springer.
Zurück zum Zitat Lu, L., Medo, M., Yeung, C. H., Zhang, Y. C., Zhang, Z. K., & Zhou, T. (2012). Recommender Systems. Physics Reports, 519(1), 1–49. Lu, L., Medo, M., Yeung, C. H., Zhang, Y. C., Zhang, Z. K., & Zhou, T. (2012). Recommender Systems. Physics Reports, 519(1), 1–49.
Zurück zum Zitat Lu, J., Wu, D., Mao, M., Wang, W., & Zhang, G. (2015). Recommender system application developments: A survey. Decision Support Systems, 74, 12–32. Lu, J., Wu, D., Mao, M., Wang, W., & Zhang, G. (2015). Recommender system application developments: A survey. Decision Support Systems, 74, 12–32.
Zurück zum Zitat Ma, H., Zhou, D., Liu, C., Lyu, M.R., King, I. (2011) Recommender Systems with Social Regularization. In: Proceedings of the fourth ACM international conference on Web search and data mining (287-296). New York: ACM. Ma, H., Zhou, D., Liu, C., Lyu, M.R., King, I. (2011) Recommender Systems with Social Regularization. In: Proceedings of the fourth ACM international conference on Web search and data mining (287-296). New York: ACM.
Zurück zum Zitat Mahmood, T., & Ricci, F. (2007). Learning and adaptivity in interactive recommender systems. In Proceedings of the ninth international conference on electronic commerce (pp. 75–84). Mahmood, T., & Ricci, F. (2007). Learning and adaptivity in interactive recommender systems. In Proceedings of the ninth international conference on electronic commerce (pp. 75–84).
Zurück zum Zitat Mahoney, M. P., Hurley, N. J., & Silvestre, G. C. M. (2006). Detecting noise in recommender system databases. In IUI '06 proceedings of the 11th international conference on intelligent user interfaces (pp. 109–115). Mahoney, M. P., Hurley, N. J., & Silvestre, G. C. M. (2006). Detecting noise in recommender system databases. In IUI '06 proceedings of the 11th international conference on intelligent user interfaces (pp. 109–115).
Zurück zum Zitat Malone, T., Grant, K., Turbak, F., Brobst, S., & Cohen, M. (1987). Intelligent information-sharing systems. Communications of the ACM, 30(5), 390–402. Malone, T., Grant, K., Turbak, F., Brobst, S., & Cohen, M. (1987). Intelligent information-sharing systems. Communications of the ACM, 30(5), 390–402.
Zurück zum Zitat Markus, L. (1997). The Qualitative Difference in Information Systems Research and Practice, In: Information Systems and Qualitative Research: Proceedings of the IFIP TC8 WG 8.2 Meeting in Philadelphia. A.S. Lee, J. Liebnau, and J.I. DeGross (eds.) (pp. 11–27). London, Chapman and Hall, Ltd. Markus, L. (1997). The Qualitative Difference in Information Systems Research and Practice, In: Information Systems and Qualitative Research: Proceedings of the IFIP TC8 WG 8.2 Meeting in Philadelphia. A.S. Lee, J. Liebnau, and J.I. DeGross (eds.) (pp. 11–27). London, Chapman and Hall, Ltd.
Zurück zum Zitat Matera, M., Rizzo, F., & Carughi, G. T. (2006). Web usability: Principles and evaluation methods. In N. Mosely & E. Mendes (Eds.), Web engineering (pp. 143–156). New York: Springer. Matera, M., Rizzo, F., & Carughi, G. T. (2006). Web usability: Principles and evaluation methods. In N. Mosely & E. Mendes (Eds.), Web engineering (pp. 143–156). New York: Springer.
Zurück zum Zitat Masthoff, J. (2011). Group Recommender Systems: Combining Individual Models. In F. Ricci, L. Rokach, B. Shapira, & P. Kantor (Eds.), Recommender Systems Handbook. Boston: Springer. Masthoff, J. (2011). Group Recommender Systems: Combining Individual Models. In F. Ricci, L. Rokach, B. Shapira, & P. Kantor (Eds.), Recommender Systems Handbook. Boston: Springer.
Zurück zum Zitat McDonald, D.W., Ackerman, M.S. (2000). Expertise recommender: a flexible recommendation system and architecture. In: CSCW ’00: Proceedings of the 2000 ACM conference on Computer supported cooperative work (pp. 231–240). New York: ACM. McDonald, D.W., Ackerman, M.S. (2000). Expertise recommender: a flexible recommendation system and architecture. In: CSCW ’00: Proceedings of the 2000 ACM conference on Computer supported cooperative work (pp. 231–240). New York: ACM.
Zurück zum Zitat McNee, S. M., Riedl, J., & Konstan, J. A. (2006). Being accurate is not enough: How accuracy metrics have hurt recommender systems. In Proceedings of CHI ‘06 extended abstracts on human factors in computing systems (pp. 1097–1101). McNee, S. M., Riedl, J., & Konstan, J. A. (2006). Being accurate is not enough: How accuracy metrics have hurt recommender systems. In Proceedings of CHI ‘06 extended abstracts on human factors in computing systems (pp. 1097–1101).
Zurück zum Zitat Mobasher, B., Burke, R., Bhaumik, R., & Williams, C. (2007). Towards trustworthy recommender systems: An analysis of attack models and algorithm robustness. ACM Transactions on Internet Technology (TOIT), 7(4), Article 23. Mobasher, B., Burke, R., Bhaumik, R., & Williams, C. (2007). Towards trustworthy recommender systems: An analysis of attack models and algorithm robustness. ACM Transactions on Internet Technology (TOIT), 7(4), Article 23.
Zurück zum Zitat Muter, I., & Aytekin, T. (2017). Incorporating aggregate diversity in recommender systems using scalable optimization approaches. Information Systems Research, 29(3), 405–421. Muter, I., & Aytekin, T. (2017). Incorporating aggregate diversity in recommender systems using scalable optimization approaches. Information Systems Research, 29(3), 405–421.
Zurück zum Zitat Narock, T., Zhou, L., & Yoon, V. (2012). Semantic similarity of ontology instances using polarity mining. Journal of the Association for Information Science and Technology, 64(2), 416–427. Narock, T., Zhou, L., & Yoon, V. (2012). Semantic similarity of ontology instances using polarity mining. Journal of the Association for Information Science and Technology, 64(2), 416–427.
Zurück zum Zitat Nielsen, J. (1993). The Usability Engineering Lifecycle. In Usability engineering. Cambridge, MA: Academic Press. Nielsen, J. (1993). The Usability Engineering Lifecycle. In Usability engineering. Cambridge, MA: Academic Press.
Zurück zum Zitat Nguyen, T. T., Maxwell Harper, F., Terveen, L., & Konstan, J. A. (2017). User personality and user satisfaction with recommender systems. Information Systems Frontiers, 20(6), 1173–1189. Nguyen, T. T., Maxwell Harper, F., Terveen, L., & Konstan, J. A. (2017). User personality and user satisfaction with recommender systems. Information Systems Frontiers, 20(6), 1173–1189.
Zurück zum Zitat Novak, J. D., & Godwin, D. B. (1984). Learning how to learn. New York: Cambridge University Press. Novak, J. D., & Godwin, D. B. (1984). Learning how to learn. New York: Cambridge University Press.
Zurück zum Zitat O’Donovan, B., & Smyth, B. (2005). Trust in recommender systems. In IUI '05 proceedings of the 10th international conference on intelligent user interfaces (pp. 167–174). O’Donovan, B., & Smyth, B. (2005). Trust in recommender systems. In IUI '05 proceedings of the 10th international conference on intelligent user interfaces (pp. 167–174).
Zurück zum Zitat O’Mahony, M., Hurley, N., Kushmerick, N., & Silvestre, G. (2004). Collaborative recommendation: a robustness analysis. ACM Transactions on Internet Technology, 4(4), 344–377. O’Mahony, M., Hurley, N., Kushmerick, N., & Silvestre, G. (2004). Collaborative recommendation: a robustness analysis. ACM Transactions on Internet Technology, 4(4), 344–377.
Zurück zum Zitat Palau, J., Montaner, M., López, B., & de la Rosa, J. L. (2004). Collaboration Analysis in Recommender Systems Using Social Networks. In M. Klusch, S. Ossowski, V. Kashyap, & R. Unland (Eds.), Cooperative Information Agents VIII. CIA 2004. Lecture Notes in Computer Science, vol (Vol. 3191). Berlin: Springer. Palau, J., Montaner, M., López, B., & de la Rosa, J. L. (2004). Collaboration Analysis in Recommender Systems Using Social Networks. In M. Klusch, S. Ossowski, V. Kashyap, & R. Unland (Eds.), Cooperative Information Agents VIII. CIA 2004. Lecture Notes in Computer Science, vol (Vol. 3191). Berlin: Springer.
Zurück zum Zitat Pan, W., Xiang E.W., Liu, N.N., Yang, Q. (2010). Transfer Learning in Collaborative Filtering for Sparsity Reduction. In: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, (AAAI-10) (230–235). Atlanta. Pan, W., Xiang E.W., Liu, N.N., Yang, Q. (2010). Transfer Learning in Collaborative Filtering for Sparsity Reduction. In: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, (AAAI-10) (230–235). Atlanta.
Zurück zum Zitat Pang, B., Lee, L., Vaithyanathan, S. (2002). Thumbs up? Sentiment classification using machine learning techniques. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) (79–86). Hanover: Now Publishers Inc. Pang, B., Lee, L., Vaithyanathan, S. (2002). Thumbs up? Sentiment classification using machine learning techniques. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) (79–86). Hanover: Now Publishers Inc.
Zurück zum Zitat Panniello, U., Gorgoglione, M., & Tuzhilin, A. (2016). In CARSs we trust: How context-aware recommendations affect customers’ trust and other business performance measures of recommender systems. Information Systems Research, 27(1), 182–196. Panniello, U., Gorgoglione, M., & Tuzhilin, A. (2016). In CARSs we trust: How context-aware recommendations affect customers’ trust and other business performance measures of recommender systems. Information Systems Research, 27(1), 182–196.
Zurück zum Zitat Park, S.-H., & Han, S. P. (2014). From accuracy to diversity in product recommendations: Relationship between diversity and customer retention. International Journal of Electronic Commerce, 18(2), 51–72. Park, S.-H., & Han, S. P. (2014). From accuracy to diversity in product recommendations: Relationship between diversity and customer retention. International Journal of Electronic Commerce, 18(2), 51–72.
Zurück zum Zitat Pathak, B., Garfinkel, R., Gopal, R. D., Venkatesh, R., & Yin, F. (2010). Empirical analysis of the impact of recommender systems on sales. Journal of Management Information Systems, 27(2), 159–188. Pathak, B., Garfinkel, R., Gopal, R. D., Venkatesh, R., & Yin, F. (2010). Empirical analysis of the impact of recommender systems on sales. Journal of Management Information Systems, 27(2), 159–188.
Zurück zum Zitat Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The adaptive decision maker. New York: Cambridge University Press. Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The adaptive decision maker. New York: Cambridge University Press.
Zurück zum Zitat Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, M. (2011). Scikit:LearnL machine learning in python. Journal of Machine Learning Research, 12, 2825–2830. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, M. (2011). Scikit:LearnL machine learning in python. Journal of Machine Learning Research, 12, 2825–2830.
Zurück zum Zitat Pennock, D. M., Horvitz, E. (2000). Collaborative filtering by personality diagnosis: A hybrid memory- and model-based approach. In: Uncertainty in Artificial Intelligence Proceedings (pp. 473-480). San Francisco: Morgan Kaufmann Publishers. Pennock, D. M., Horvitz, E. (2000). Collaborative filtering by personality diagnosis: A hybrid memory- and model-based approach. In: Uncertainty in Artificial Intelligence Proceedings (pp. 473-480). San Francisco: Morgan Kaufmann Publishers.
Zurück zum Zitat Peska, L., & Vojtas, P. (2017). Using implicit preference relations to improve content based recommending. Journal on Data Semantics, 6(1), 15–30. Peska, L., & Vojtas, P. (2017). Using implicit preference relations to improve content based recommending. Journal on Data Semantics, 6(1), 15–30.
Zurück zum Zitat Pollock, J. T., & Hodgson, R. (2004). Ontology design patterns. Adaptive Information: Improving Business through Semantic Interoperability, Grid Computing, and Enterprise Integration (pp. 145–194). Chichester: John Wiley & Sons. Pollock, J. T., & Hodgson, R. (2004). Ontology design patterns. Adaptive Information: Improving Business through Semantic Interoperability, Grid Computing, and Enterprise Integration (pp. 145–194). Chichester: John Wiley & Sons.
Zurück zum Zitat Portugal, I., Alencat, P., & Cowan, D. (2018). The use of machine learning algorithms in recommender systems: A systematic review. Expert Systems with Applications, 97, 205–227. Portugal, I., Alencat, P., & Cowan, D. (2018). The use of machine learning algorithms in recommender systems: A systematic review. Expert Systems with Applications, 97, 205–227.
Zurück zum Zitat Porzel R, Malaka R (2004) A task-based approach for ontology evaluation. In: Proceeding of ECAI 2004 workshop on ontology learning and population, Valencia, Spain. Porzel R, Malaka R (2004) A task-based approach for ontology evaluation. In: Proceeding of ECAI 2004 workshop on ontology learning and population, Valencia, Spain.
Zurück zum Zitat Pu, P., Chen, L., & Hu, R. (2011). A user-centric evaluation framework for recommender systems. In RecSys '11 proceedings of the fifth ACM conference on recommender systems (pp. 157–164). Pu, P., Chen, L., & Hu, R. (2011). A user-centric evaluation framework for recommender systems. In RecSys '11 proceedings of the fifth ACM conference on recommender systems (pp. 157–164).
Zurück zum Zitat Rad, H.S., Lucas, C. (2007). A recommender system based on invasive weed optimization algorithm. IEEE Congress on Evolutionary Computation, CEC 2007, (pp. 4297–4304). Singapore: IEEE. Rad, H.S., Lucas, C. (2007). A recommender system based on invasive weed optimization algorithm. IEEE Congress on Evolutionary Computation, CEC 2007, (pp. 4297–4304). Singapore: IEEE.
Zurück zum Zitat Raad, J., Cruz, C. (2015). A survey of ontology evaluation methods. In: Proceedings of the International Conference on Knowledge Engineering and Ontology Development, part of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Lisbonne, Portugal. Raad, J., Cruz, C. (2015). A survey of ontology evaluation methods. In: Proceedings of the International Conference on Knowledge Engineering and Ontology Development, part of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Lisbonne, Portugal.
Zurück zum Zitat Rashid, A. M.,Albert, I., Cosley, D., Lam, S. K., McNee, S. M., Konstan, J. A., Riedl, J. (2002). Getting to Know You: Learning New User Preferences in Recommender Systems. In: Proceedings of the International Conference on Intelligent User Interfaces (pp. 127-134). New York: ACM Press. Rashid, A. M.,Albert, I., Cosley, D., Lam, S. K., McNee, S. M., Konstan, J. A., Riedl, J. (2002). Getting to Know You: Learning New User Preferences in Recommender Systems. In: Proceedings of the International Conference on Intelligent User Interfaces (pp. 127-134). New York: ACM Press.
Zurück zum Zitat Ramaprasad, A., & Syn, T. (2015). Ontological Meta-analysis and synthesis. Communications of the Association of Information Systems, 37(7), 138–153. Ramaprasad, A., & Syn, T. (2015). Ontological Meta-analysis and synthesis. Communications of the Association of Information Systems, 37(7), 138–153.
Zurück zum Zitat Rao, L., Mansingh, G., & Osei-Bryson, K.-M. (2012). Building ontology based knowledge maps to assist business process re-engineering. Decision Support Systems., 52(3), 577–589. Rao, L., Mansingh, G., & Osei-Bryson, K.-M. (2012). Building ontology based knowledge maps to assist business process re-engineering. Decision Support Systems., 52(3), 577–589.
Zurück zum Zitat Resnick, P., & Varian, H. R. (1997). Recommender systems. Communications of the ACM, 40(3), 56–58. Resnick, P., & Varian, H. R. (1997). Recommender systems. Communications of the ACM, 40(3), 56–58.
Zurück zum Zitat Resnick, P., & Sami, R. (2008). Manipulation-resistant recommender systems through influence limits. ACM SIGecom Exchanges, 7(3), 1–4. Resnick, P., & Sami, R. (2008). Manipulation-resistant recommender systems through influence limits. ACM SIGecom Exchanges, 7(3), 1–4.
Zurück zum Zitat Ricci, F. (2002). Travel recommender systems. IEEE Intelligent Systems, 55–57. Ricci, F. (2002). Travel recommender systems. IEEE Intelligent Systems, 55–57.
Zurück zum Zitat Rong, W., Peng, B., Ouyang, Y., Liu, K., & Xiong, Z. (2015). Collaborative personal profiling for web service ranking and recommendation. Information Systems Frontiers, 17(6), 1265–1282. Rong, W., Peng, B., Ouyang, Y., Liu, K., & Xiong, Z. (2015). Collaborative personal profiling for web service ranking and recommendation. Information Systems Frontiers, 17(6), 1265–1282.
Zurück zum Zitat Ruiz-Primo, M., & Shavelson, R. (1996). Problems and issues in the use of concept maps in science assessment. Journal of Research in Science Teaching, 33(6), 569–600. Ruiz-Primo, M., & Shavelson, R. (1996). Problems and issues in the use of concept maps in science assessment. Journal of Research in Science Teaching, 33(6), 569–600.
Zurück zum Zitat Sahoo, N., Singh, P. V., & Mukhopadhyay, T. (2012). A hidden Markov model for collaborative filtering. MIS Quarterly, 36(4), 1329. Sahoo, N., Singh, P. V., & Mukhopadhyay, T. (2012). A hidden Markov model for collaborative filtering. MIS Quarterly, 36(4), 1329.
Zurück zum Zitat Saldana, J. (2016). The coding manual for qualitative researchers. Sage Publications, Thousands Oaks, CA USA. Saldana, J. (2016). The coding manual for qualitative researchers. Sage Publications, Thousands Oaks, CA USA.
Zurück zum Zitat Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2000a). Analysis of recommendation algorithms for E-commerce. In Proceedings of the 2nd ACM conference on electronic commerce (pp. 158–167). Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2000a). Analysis of recommendation algorithms for E-commerce. In Proceedings of the 2nd ACM conference on electronic commerce (pp. 158–167).
Zurück zum Zitat Sehlimmer, J. C., Granger, R. H. (1986). Beyond incremental processing: Tracking concept drift. In: Proceedings of the Fifth National Conference on Artificial Intelligence (pp. 502-507). Philadelphia: Morgan Kaufmann. Sehlimmer, J. C., Granger, R. H. (1986). Beyond incremental processing: Tracking concept drift. In: Proceedings of the Fifth National Conference on Artificial Intelligence (pp. 502-507). Philadelphia: Morgan Kaufmann.
Zurück zum Zitat Schafer, J. B., Konstan, J. A., & Riedl, J. (2001). E-commerce recommendation applications. In Applications of data mining to electronic commerce (pp. 115–153). Schafer, J. B., Konstan, J. A., & Riedl, J. (2001). E-commerce recommendation applications. In Applications of data mining to electronic commerce (pp. 115–153).
Zurück zum Zitat Schafer, J.B., Frankowski, D., Herlocker, J., Sen, S. (2007). Collaborative filtering recommender systems. In: P. Brusilovsky, A. Kobsa, W. Nejdl (Eds.), The Adaptive Web. Springer, Berlin 2007, 291–324. Schafer, J.B., Frankowski, D., Herlocker, J., Sen, S. (2007). Collaborative filtering recommender systems. In: P. Brusilovsky, A. Kobsa, W. Nejdl (Eds.), The Adaptive Web. Springer, Berlin 2007, 291–324.
Zurück zum Zitat Shani, G., Heckerman, D., & Brafman, R. I. (2005). An MDP-based recommender system. Journal of Machine Learning Research, 6, 1265–1295. Shani, G., Heckerman, D., & Brafman, R. I. (2005). An MDP-based recommender system. Journal of Machine Learning Research, 6, 1265–1295.
Zurück zum Zitat Schein, A. I., Popescul, A., Ungar, L. H., & Pennock, D. M. (2002). Methods and metrics for cold-start recommendations. In SIGIR '02 proceedings of the 25th annual international ACM SIGIR conference on research and development in information retrieval (pp. 253–260). Schein, A. I., Popescul, A., Ungar, L. H., & Pennock, D. M. (2002). Methods and metrics for cold-start recommendations. In SIGIR '02 proceedings of the 25th annual international ACM SIGIR conference on research and development in information retrieval (pp. 253–260).
Zurück zum Zitat Sie, R. L. L., Bitter-Rijpkema, M., & Sloep, P. B. (2010). A simulation for content-based and utility-based recommendation of candidate coalitions in virtual creativity teams. Procedia Computer Science, 1(2), 2883–2888. Sie, R. L. L., Bitter-Rijpkema, M., & Sloep, P. B. (2010). A simulation for content-based and utility-based recommendation of candidate coalitions in virtual creativity teams. Procedia Computer Science, 1(2), 2883–2888.
Zurück zum Zitat Simon, H. (1955). A behavioral model of choice. Quarterly Journal of Economics, 69(1), 99–118. Simon, H. (1955). A behavioral model of choice. Quarterly Journal of Economics, 69(1), 99–118.
Zurück zum Zitat Smyth, B., McClave, P. (2001). Similarity vs diversity. In: Proceedings of the 4th International Conference on Case-Based Reasoning (pp. 347-361). Berlin: Springer-Verlag. Smyth, B., McClave, P. (2001). Similarity vs diversity. In: Proceedings of the 4th International Conference on Case-Based Reasoning (pp. 347-361). Berlin: Springer-Verlag.
Zurück zum Zitat Starr, R. R., & de Oliveira, J. M. P. (2013). Concept maps as the first step in ontology creation. Information Systems, 38(5), 771–783. Starr, R. R., & de Oliveira, J. M. P. (2013). Concept maps as the first step in ontology creation. Information Systems, 38(5), 771–783.
Zurück zum Zitat Strasunskas D, Tomassen S (2008) Empirical insights on a value of ontology quality in ontology-driven web search. OnTheMove 2008 confederated international conferences (OTM 2008), Monterrey, Mexico (pp 1319–1337). Strasunskas D, Tomassen S (2008) Empirical insights on a value of ontology quality in ontology-driven web search. OnTheMove 2008 confederated international conferences (OTM 2008), Monterrey, Mexico (pp 1319–1337).
Zurück zum Zitat Suárez-Figueroa, M. C., Gómez-Pérez, A., & Fernández-López, M. (2012). The NeOn methodology for ontology engineering. In M. Suárez-Figueroa, A. Gómez-Pérez, E. Motta, & A. Gangemi (Eds.), Ontology engineering in a networked world. Berlin, Heidelberg: Springer. Suárez-Figueroa, M. C., Gómez-Pérez, A., & Fernández-López, M. (2012). The NeOn methodology for ontology engineering. In M. Suárez-Figueroa, A. Gómez-Pérez, E. Motta, & A. Gangemi (Eds.), Ontology engineering in a networked world. Berlin, Heidelberg: Springer.
Zurück zum Zitat Tao, L., Cao, J., & Liu, F. (2017). Quantifying textual terms for similarity measurement. Information Sciences, 415-416, 269–282. Tao, L., Cao, J., & Liu, F. (2017). Quantifying textual terms for similarity measurement. Information Sciences, 415-416, 269–282.
Zurück zum Zitat Thieblin, E., Haemmerle, O., Trojahn, C. (2018). Complex matching based on competency questions for alignment: a first sketch. Emerging Topics in Semantic Technologies. ISWC 2018 Satellite Events. E. Demidova, A.J. Zaveri, E. Simperl (Eds.), ISBN: 978–3–89838-736-1, 2018, AKA Verlag Berlin. Thieblin, E., Haemmerle, O., Trojahn, C. (2018). Complex matching based on competency questions for alignment: a first sketch. Emerging Topics in Semantic Technologies. ISWC 2018 Satellite Events. E. Demidova, A.J. Zaveri, E. Simperl (Eds.), ISBN: 978–3–89838-736-1, 2018, AKA Verlag Berlin.
Zurück zum Zitat Tintarev, N., & Masthoff, J. (2007). Survey of explanations in recommender systems. 2007 IEEE 23rd International Conference on Data Engineering Workshop (pp. 801–810). Tintarev, N., & Masthoff, J. (2007). Survey of explanations in recommender systems. 2007 IEEE 23rd International Conference on Data Engineering Workshop (pp. 801–810).
Zurück zum Zitat Tuzhilin, A. (2012). Customer relationship management and web mining: The next frontier. Data Mining and Knowledge Discovery, 24(3), 584–612. Tuzhilin, A. (2012). Customer relationship management and web mining: The next frontier. Data Mining and Knowledge Discovery, 24(3), 584–612.
Zurück zum Zitat Tuzlukov, V. (2010). Signal processing noise. Electrical Engineering and Applied Signal Processing Series, CRC press. Tuzlukov, V. (2010). Signal processing noise. Electrical Engineering and Applied Signal Processing Series, CRC press.
Zurück zum Zitat Vargas, S., Castells, P. (2014). Improving sales diversity by recommending users to items. In: Proceedings of the 8th ACM Conference on Recommender Systems (pp. 145–152). New York: ACM. Vargas, S., Castells, P. (2014). Improving sales diversity by recommending users to items. In: Proceedings of the 8th ACM Conference on Recommender Systems (pp. 145–152). New York: ACM.
Zurück zum Zitat Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Zurück zum Zitat Verbert, K., Manousellis, N., Ochoa, X., Wolpers, M., Drachsler, H., Bosnic, I., & Duval, E. (2012). Context-aware recommender Systems for Learning: A survey and future challenges. IEEE Transactions on Learning Technologies, 5(4), 318–335. Verbert, K., Manousellis, N., Ochoa, X., Wolpers, M., Drachsler, H., Bosnic, I., & Duval, E. (2012). Context-aware recommender Systems for Learning: A survey and future challenges. IEEE Transactions on Learning Technologies, 5(4), 318–335.
Zurück zum Zitat Vrandecic, D., Pinto, S., Tempich, C., & Sure, Y. (2005). The diligent knowledge processes. Journal of Knowledge Processes, 9(5), 85–96. Vrandecic, D., Pinto, S., Tempich, C., & Sure, Y. (2005). The diligent knowledge processes. Journal of Knowledge Processes, 9(5), 85–96.
Zurück zum Zitat Wang, H., Wang, N., & Yeung, D. (2015). Collaborative deep learning for recommender systems. In KDD '15 proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1235–1244). Wang, H., Wang, N., & Yeung, D. (2015). Collaborative deep learning for recommender systems. In KDD '15 proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1235–1244).
Zurück zum Zitat Wang, Y. F., Chiang, D. A., Hsu, M. H., Lin, C. J., & Lin, I. L. (2009). A recommender system to avoid customer churn: A case study. Expert Systems with Applications, 36, 8071–8075. Wang, Y. F., Chiang, D. A., Hsu, M. H., Lin, C. J., & Lin, I. L. (2009). A recommender system to avoid customer churn: A case study. Expert Systems with Applications, 36, 8071–8075.
Zurück zum Zitat Warren, C., McGraw, A. P., & Van Boven, L. (2011). Values and preferences: defining preference construction. Wiley Interdisciplinary Reviews: Cognitive Science, 2(2), 193–205. Warren, C., McGraw, A. P., & Van Boven, L. (2011). Values and preferences: defining preference construction. Wiley Interdisciplinary Reviews: Cognitive Science, 2(2), 193–205.
Zurück zum Zitat Wong, W., Liu, W., & Bennamoun, M. (2012). Ontology learning from text: A look back and into the future. ACM Computer Surveys, 44(4), Article 20. Wong, W., Liu, W., & Bennamoun, M. (2012). Ontology learning from text: A look back and into the future. ACM Computer Surveys, 44(4), Article 20.
Zurück zum Zitat Xiao, B., & Benbasat, I. (2007). E-commerce product recommendation agents: Use, characteristics, and impact. MIS Quarterly, 31(1), 137–209. Xiao, B., & Benbasat, I. (2007). E-commerce product recommendation agents: Use, characteristics, and impact. MIS Quarterly, 31(1), 137–209.
Zurück zum Zitat Yang, X., Guo, Y., Liu, Y., & Steck, H. (2014). A survey of collaborative filtering based social recommender systems. Computer Communications, 41, 1–10. Yang, X., Guo, Y., Liu, Y., & Steck, H. (2014). A survey of collaborative filtering based social recommender systems. Computer Communications, 41, 1–10.
Zurück zum Zitat Yao, Y. Y. (1995). Measuring retrieval effectiveness based on user preference of documents. Journal of the American Society for Information Science, 46, 133–145. Yao, Y. Y. (1995). Measuring retrieval effectiveness based on user preference of documents. Journal of the American Society for Information Science, 46, 133–145.
Zurück zum Zitat Yoon, V. Y., Hostler, R. E., Guo, Z., & Guimares, T. (2013). Assessing the moderating effect of consumer product knowledge and online shopping experience on using recommendation agents for customer loyalty. Decision Support Systems, 55(4), 883–893. Yoon, V. Y., Hostler, R. E., Guo, Z., & Guimares, T. (2013). Assessing the moderating effect of consumer product knowledge and online shopping experience on using recommendation agents for customer loyalty. Decision Support Systems, 55(4), 883–893.
Zurück zum Zitat Zibriczky, D. (2016) Recommender Systems meet Finance: A literature review. In: Proceedings of the 2nd International Workshop on Personalization & Recommender Systems in Financial Services, Bari. Zibriczky, D. (2016) Recommender Systems meet Finance: A literature review. In: Proceedings of the 2nd International Workshop on Personalization & Recommender Systems in Financial Services, Bari.
Zurück zum Zitat Zimmermann, A., Lorenz, & Oppermann. (2007). An operational definition of context. In modeling and using context: 6th international and interdisciplinary conference, CONTEXT 2007, Roskilde, Denmark, august 20-24, 2007. Proceedings (Vol. 4635, lecture notes in computer science, pp. 558-571). Berlin, Heidelberg: Springer Berlin Heidelberg. Zimmermann, A., Lorenz, & Oppermann. (2007). An operational definition of context. In modeling and using context: 6th international and interdisciplinary conference, CONTEXT 2007, Roskilde, Denmark, august 20-24, 2007. Proceedings (Vol. 4635, lecture notes in computer science, pp. 558-571). Berlin, Heidelberg: Springer Berlin Heidelberg.
Metadaten
Titel
RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers
verfasst von
Lawrence Bunnell
Kweku-Muata Osei-Bryson
Victoria Y. Yoon
Publikationsdatum
25.06.2019
Verlag
Springer US
Erschienen in
Information Systems Frontiers / Ausgabe 6/2020
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-019-09935-9

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