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2016 | OriginalPaper | Chapter

Enriching Preferences Using DBpedia and Wordnet

Authors : Okan Bursa, Özgü Can, Emine Sezer, Murat Osman Ünalır

Published in: Metadata and Semantics Research

Publisher: Springer International Publishing

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Abstract

In Facebook, every like and interest is a preference. A like is an act of acknowledgement, which can be valuable if it is processed rightfully. In this work, the Facebook Page Like preferences of users are captured and these preferences are enriched by matching them with DBpedia and DaKick entities. To semantify these Facebook preferences, the free text search abilities of DBpedia and Allegrograph are used. WordNet is used to find the word similarities between preferences and ontology entities and evaluate the similarity for matching. Matched preferences are stored in FOAF profiles and two new ontologies are presented. SociaLike ontology is created to describe each preference with its properties and connections. Facebook profiles are converted into FOAF profiles and Facebook page information is stored inside the new FacebookAPI ontology. FOAF, SociaLike and FacebookAPI ontologies are used together to define user profile, represent and store user preferences.

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Footnotes
Literature
1.
Mirizzi, R., Di Noia, T., Ragone, A., Claudio Ostuni, V., Di Sciascio, E.: Movie recommendation with DBpedia. In: CEUR Workshop Proceedings, vol. 835, pp. 101–112 (2012)
2.
Paulo Leal, J., Rodrigues, V., Queirós, R.: Computing semantic relatedness using DBPedia. In: 1st Symposium on Languages, Applications and Technologies (SLATE 2012), pp. 133–147 (2012)
3.
Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)CrossRef
4.
Bizer, C., Heath, T., Berners-Lee, T.: Linked data - the story so far. Int. J. Semant. Web Inf. Syst. 5(3), 1–22 (2009)CrossRef
5.
Eyharabide, V., Amandi, A.: Ontology-based user profile learning. Appl. Intell. 36(4), 857–869 (2012)CrossRef
6.
Weaver, J., Tarjan, P.: Facebook linked data via the graph API. Semant. Web 4(3), 245–250 (2013)
7.
Sato, T., Fujita, M., Kobayashi, M., Ito, K.: Recommender system by grasping individual preference and influence from other users. In: Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM 2013, pp. 1345–1351 (2013)
8.
Cantador, I., Castells, P., Bellog’ın, A.: An enhanced semantic layer for hybrid recommender systems: application to news recommendation. Int. J. Semant. Web Inf. Syst. 7(1), 44–78 (2011)CrossRef
9.
Krauss, C., Braun, S., Arbanowski, S.: Preference ontologies based on social media for compensating the cold start problem. In: Proceedings of the 8th Workshop on Social Network Mining, Analysis, SNAKDD 2014, New York, NY, USA, pp. 12:1–12:4. ACM (2014)
10.
Wittkower, D.E.: Facebook and Philosophy: What’s on Your Mind?. Popular Culture and Philosophy. Open Court, Chicago (2010)
11.
Bursa, O., Sezer, E., Can, O., Unalir, M.O.: Using FOAF for interoperable and privacy protected healthcare information systems. In: Closs, S., Studer, R., Garoufallou, E., Sicilia, M.-A. (eds.) MTSR 2014. CCIS, vol. 478, pp. 154–161. Springer, Heidelberg (2014). doi:10.​1007/​978-3-319-13674-5_​15
12.
Dong, X., Gabrilovich, E., Heitz, G., Horn, W., Lao, N., Murphy, K., Strohmann, T., Sun, S., Zhang, W.: Knowledge vault: a web-scale approach to probabilistic knowledge fusion. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2014, New York, NY, USA, pp. 601–610. ACM (2014)
13.
Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, New York, NY, USA, pp. 697–706. ACM (2007)
Metadata
Title
Enriching Preferences Using DBpedia and Wordnet
Authors
Okan Bursa
Özgü Can
Emine Sezer
Murat Osman Ünalır
Copyright Year
2016
Book
Metadata and Semantics Research

Print ISBN: 978-3-319-49156-1

Electronic ISBN: 978-3-319-49157-8

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-49157-8_8