Skip to main content

2018 | OriginalPaper | Buchkapitel

MAICBR: A Multi-agent Intelligent Content-Based Recommendation System

verfasst von : Aarti Singh, Anu Sharma

Erschienen in: Information and Communication Technology for Sustainable Development

Verlag: Springer Singapore

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This study aims at proposing an intelligent and adaptive mechanism deploying intelligent agents for solving new user and overspecialization problems that exist in Content Based Recommendation (CBR) systems. Since the system is designed using software agents (SAs), it ensures highly desired full automation in web recommendations. The proposed system has been evaluated and the results suggested that there is an improvement in positive feedback rate and the decrease in recommendation rate.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Singh, A., Sharma, A., Dey, N.: Semantics and agents oriented web personalization –state of the art. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 6(2), 35–49 (2015) Singh, A., Sharma, A., Dey, N.: Semantics and agents oriented web personalization –state of the art. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 6(2), 35–49 (2015)
2.
Zurück zum Zitat Park, D. H., Kim, H. K., Choi, I. Y., Kim, J. K.: A literature review and classification of recommender systems research. Expert Syst. App., 39, 10059–10072 (2012) Park, D. H., Kim, H. K., Choi, I. Y., Kim, J. K.: A literature review and classification of recommender systems research. Expert Syst. App., 39, 10059–10072 (2012)
3.
Zurück zum Zitat Anand, S. S., Mobasher, B.: Intelligent Techniques for Web Personalization. In: Intelligent Techniques for Web Personalization, Springer, 1–36 (2005) Anand, S. S., Mobasher, B.: Intelligent Techniques for Web Personalization. In: Intelligent Techniques for Web Personalization, Springer, 1–36 (2005)
4.
Zurück zum Zitat Sarwar, B. M., Konstan, J. A., Borchers, N., HerIocker, J., Miller, B. Miller, Riedl, J.: Using Filtering Agents to Improve Prediction Quality in the GroupLens Research Collaborative Filtering System, In: Proceedings in CSCW’98 Seattle, Washington, USA, 345–354 (1998) Sarwar, B. M., Konstan, J. A., Borchers, N., HerIocker, J., Miller, B. Miller, Riedl, J.: Using Filtering Agents to Improve Prediction Quality in the GroupLens Research Collaborative Filtering System, In: Proceedings in CSCW’98 Seattle, Washington, USA, 345–354 (1998)
5.
Zurück zum Zitat Debnath, S., Ganguly, N., Mitra P.: Feature Weighting in Content Based Recommendation System Using Social Network Analysis, In: Proceedings in WWW 2008, Beijing, China, 1041–1042 (2008) Debnath, S., Ganguly, N., Mitra P.: Feature Weighting in Content Based Recommendation System Using Social Network Analysis, In: Proceedings in WWW 2008, Beijing, China, 1041–1042 (2008)
6.
Zurück zum Zitat Eirinaki, M., Vazirgiannis, M., Varlamis, I.: SEWeP: Using Site Semantics and a Taxonomy to Enhance the Web Personalization Process, In: Proceedings in SIGKDD ’03, Washington DC, USA, 99–108 (2003) Eirinaki, M., Vazirgiannis, M., Varlamis, I.: SEWeP: Using Site Semantics and a Taxonomy to Enhance the Web Personalization Process, In: Proceedings in SIGKDD ’03, Washington DC, USA, 99–108 (2003)
7.
Zurück zum Zitat Singh, A. Juneja, D., Sharma, A. K.: Design of an intelligent and adaptive mapping mechanism for multiagent Interface. In: proceedings in International Conference on High Performance Architecture and Grid Computing (HPAGC’11), 373–384 (2011) Singh, A. Juneja, D., Sharma, A. K.: Design of an intelligent and adaptive mapping mechanism for multiagent Interface. In: proceedings in International Conference on High Performance Architecture and Grid Computing (HPAGC’11), 373–384 (2011)
8.
Zurück zum Zitat Albayrak, S., Wollny, S., Varone, N., Lommatzsch, A., Milosevic, D.: Agent Technology for Personalized Information Filtering: The PIA-System. In: ACM Symposium on Applied Computing, 54–59 (2005) Albayrak, S., Wollny, S., Varone, N., Lommatzsch, A., Milosevic, D.: Agent Technology for Personalized Information Filtering: The PIA-System. In: ACM Symposium on Applied Computing, 54–59 (2005)
9.
Zurück zum Zitat Miao, C, Yang Q., Fang H., Goh. A.: A cognitive approach for agent-based personalized recommendation. Knowl-Based Syst., 20(4), 397–405 (2007) Miao, C, Yang Q., Fang H., Goh. A.: A cognitive approach for agent-based personalized recommendation. Knowl-Based Syst., 20(4), 397–405 (2007)
10.
Zurück zum Zitat Huang, L., Dai, L., Wei, Y., Huang, M.: A personalized recommendation system based on multi-Agent. In: Proceedings in Second International Conference on Genetic and Evolutionary Computing, 223–226 (2008) Huang, L., Dai, L., Wei, Y., Huang, M.: A personalized recommendation system based on multi-Agent. In: Proceedings in Second International Conference on Genetic and Evolutionary Computing, 223–226 (2008)
11.
Zurück zum Zitat Pan, P., Wang, C., Horng, G., Cheng, S.: The Development of an ontology-based adaptive personalized recommender system, In: Proceedings in International Conference on Electronics and Information Engineering (ICEIE 2010), vol. 1, V176–V180 (2010) Pan, P., Wang, C., Horng, G., Cheng, S.: The Development of an ontology-based adaptive personalized recommender system, In: Proceedings in International Conference on Electronics and Information Engineering (ICEIE 2010), vol. 1, V176–V180 (2010)
12.
Zurück zum Zitat Ge, J., Chen, Z., Peng, J., Li, T.: An ontology-based method for personalized recommendation. In: Proceedings in 11th IEEE Int. Conf. on Cognitive Informatics & Cognitive Computing, 522–526 (2012) Ge, J., Chen, Z., Peng, J., Li, T.: An ontology-based method for personalized recommendation. In: Proceedings in 11th IEEE Int. Conf. on Cognitive Informatics & Cognitive Computing, 522–526 (2012)
13.
Zurück zum Zitat Blanco-Fernández, Y., López-Nores, M., Gil-Solla, A., Ramos-Cabrer, M., Pazos-Arias, J. J.: Exploring synergies between content-based filtering and spreading activation techniques in knowledge-based recommender systems. Inform Sciences, 181(21), 4823–4846 (2011) Blanco-Fernández, Y., López-Nores, M., Gil-Solla, A., Ramos-Cabrer, M., Pazos-Arias, J. J.: Exploring synergies between content-based filtering and spreading activation techniques in knowledge-based recommender systems. Inform Sciences, 181(21), 4823–4846 (2011)
14.
Zurück zum Zitat Kahara, T., Haataja, K., Toivanen, P.: Towards more accurate and intelligent recommendation Systems. In: Proceedings in 13th International Conference on Intelligent Systems Design and Applications (ISDA), 165–171 (2013) Kahara, T., Haataja, K., Toivanen, P.: Towards more accurate and intelligent recommendation Systems. In: Proceedings in 13th International Conference on Intelligent Systems Design and Applications (ISDA), 165–171 (2013)
15.
Zurück zum Zitat Maleszka, M., Mianowska, B., Nguyen, N. T.: A method for collaborative recommendation using knowledge integration tools and hierarchical structure of user profiles. Knowl-Based Syst., 47, 1–13 (2013) Maleszka, M., Mianowska, B., Nguyen, N. T.: A method for collaborative recommendation using knowledge integration tools and hierarchical structure of user profiles. Knowl-Based Syst., 47, 1–13 (2013)
16.
Zurück zum Zitat Han, J., M. Kamber: Data Mining: Concepts and Techniques, 2nd edition, Morgan Kaufmann Publisher, ISBN 1-55860-901-6. (2006) Han, J., M. Kamber: Data Mining: Concepts and Techniques, 2nd edition, Morgan Kaufmann Publisher, ISBN 1-55860-901-6. (2006)
17.
Zurück zum Zitat Rocha, C., Schawabe, D., Poggi, M.: A hybrid approach for searching in the semantic web. In: Proceedings in 13th International World Wide Web Conference (WWW-04), 74–84 (2004) Rocha, C., Schawabe, D., Poggi, M.: A hybrid approach for searching in the semantic web. In: Proceedings in 13th International World Wide Web Conference (WWW-04), 74–84 (2004)
18.
Zurück zum Zitat Anyanwu, K., Sheth A.: ρ-Queries: enabling querying for semantic associations on the semantic web. In: 12th International World Wide Web Conference (WWW-03), 115–125 (2003) Anyanwu, K., Sheth A.: ρ-Queries: enabling querying for semantic associations on the semantic web. In: 12th International World Wide Web Conference (WWW-03), 115–125 (2003)
Metadaten
Titel
MAICBR: A Multi-agent Intelligent Content-Based Recommendation System
verfasst von
Aarti Singh
Anu Sharma
Copyright-Jahr
2018
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-3920-1_41

Premium Partner