Affiliations: Department of Computer Engineering, Yeungnam University, Gyeongsan, Korea | Department of Computer Engineering, Chung-Ang University, Seoul, Korea
Note: [] This work has been conducted when the author was in Yeungnam University, Korea. Corresponding author. Jason J. Jung, Department of Computer Engineering, Chung-Ang University, Seoul, Korea. Tel.: +82 53 810 3534; Fax: +82 53 810 4630; E-mails: [email protected] (Jason J. Jung); [email protected] (Xuan Hau Pham).
Abstract: Since we have been facing multilingual contents, it is difficult for recommender systems (RecSys) to efficiently collect user feedbacks (e.g., ratings). Thus, we expect that multilingual entities matching can improve the performance of recommendation services. Particularly, in movie recommendation services, the movies have several titles in different languages. Thereby, we are focusing on interlinking some possible data sources including traditional tabular data (e.g., IMDB) and Linked Open Data (LOD) (e.g., DBpedia and LinkedMDB). This paper shows meaningful experiences that we have observed during experimentation; i) discovering identical movies which have multilingual titles by interlinking LOD, and ii) improving the performance of multilingual recommendation.
