Recommendation system based on multilingual entity matching on linked open data
- Authors
- Xuan Hau Pham; Jung, Jason J.
- Issue Date
- 2014
- Publisher
- IOS PRESS
- Keywords
- Linked open data; interlinks; string matching; recommendation systems; multilingual entity
- Citation
- JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, v.27, no.2, pp 589 - 599
- Pages
- 11
- Journal Title
- JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
- Volume
- 27
- Number
- 2
- Start Page
- 589
- End Page
- 599
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/13980
- DOI
- 10.3233/IFS-131044
- ISSN
- 1064-1246
1875-8967
- 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.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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