Generic knowledge-based analysis of social media for recommendations

V. de Graaff, Anne van de Venis, Maurice van Keulen, R.A. de By

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Abstract

Recommender systems have been around for decades to help people find the best matching item in a pre-defined item set. Knowledge-based recommender systems are used to match users based on information that links the two, but they often focus on a single, specific application, such as movies to watch or music to listen to. In this presentation, we present our Interest-Based Recommender System (IBRS). This knowledge-based recommender system provides recommendations that are generic in three dimensions: IBRS is (1) domain-independent, (2) language-independent, and (3) independent of the used social medium. To match user interests with items, the first are derived from the user's social media profile, enriched with a deeper semantic embedding obtained from the generic knowledge base DBpedia. These interests are used to extract personalized recommendations from a tagged item set from any domain, in any language. We also present the results of a validation of IBRS by a test user group of 44 people using two item sets from separate domains: greeting cards and holiday homes.
Original languageEnglish
Title of host publicationCBRecSys 2015, New Trends on Content-Based Recommender Systems
Subtitle of host publicationProceedings of the 2nd Workshop on New Trends on Content-Based Recommender Systems co-located with 9th ACM Conference on Recommender Systems (RecSys 2015)
EditorsToine Bogers, Marijn Koolen
Place of PublicationNew York
PublisherCEUR
Pages22-29
Number of pages8
Publication statusPublished - 20 Sep 2015
Event2nd Workshop on New Trends in Content-Based Recommender Systems, CBRecSys 2015 - Vienna, Austria
Duration: 16 Sep 201520 Sep 2015
Conference number: 2
http://ceur-ws.org/Vol-1448/

Publication series

NameCEUR Workshop Proceedings
Volume1448
ISSN (Electronic)1613-0073

Workshop

Workshop2nd Workshop on New Trends in Content-Based Recommender Systems, CBRecSys 2015
Abbreviated titleCBRecSys 2015
CountryAustria
CityVienna
Period16/09/1520/09/15
Internet address

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Keywords

  • EWI-26160
  • IR-96988
  • METIS-312679

Cite this

de Graaff, V., van de Venis, A., van Keulen, M., & de By, R. A. (2015). Generic knowledge-based analysis of social media for recommendations. In T. Bogers, & M. Koolen (Eds.), CBRecSys 2015, New Trends on Content-Based Recommender Systems: Proceedings of the 2nd Workshop on New Trends on Content-Based Recommender Systems co-located with 9th ACM Conference on Recommender Systems (RecSys 2015) (pp. 22-29). (CEUR Workshop Proceedings; Vol. 1448). New York: CEUR.