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.
|Title of host publication||CBRecSys 2015, New Trends on Content-Based Recommender Systems|
|Subtitle of host publication||Proceedings of the 2nd Workshop on New Trends on Content-Based Recommender Systems co-located with 9th ACM Conference on Recommender Systems (RecSys 2015)|
|Editors||Toine Bogers, Marijn Koolen|
|Place of Publication||New York|
|Number of pages||8|
|Publication status||Published - 20 Sep 2015|
|Event||2nd Workshop on New Trends in Content-Based Recommender Systems, CBRecSys 2015 - Vienna, Austria|
Duration: 16 Sep 2015 → 20 Sep 2015
Conference number: 2
|Name||CEUR Workshop Proceedings|
|Workshop||2nd Workshop on New Trends in Content-Based Recommender Systems, CBRecSys 2015|
|Abbreviated title||CBRecSys 2015|
|Period||16/09/15 → 20/09/15|
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.