Recommendation system based on multilingual entity matching on linked open data

Title
Recommendation system based on multilingual entity matching on linked open data
Author(s)
정재은팜하우슈엔
Keywords
MANAGEMENT-SYSTEM; INFORMATION; NETWORKS; ONTOLOGY; WEB
Issue Date
201408
Publisher
IOS PRESS
Citation
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, v.27, no.2, pp.589 - 599
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.
URI
http://hdl.handle.net/YU.REPOSITORY/31188http://dx.doi.org/10.3233/IFS-131044
ISSN
1064-1246
Appears in Collections:
공과대학 > 컴퓨터공학과 > Articles
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