Using Wikipedia to alleviate data sparsity issues in Recommender Systems
|Using Wikipedia to alleviate data sparsity issues in Recommender Systems|
|Author(s)||Loizou A., Dasmahapatra S.|
|Published in||Proceedings - 2010 5th International Workshop on Semantic Media Adaptation and Personalization, SMAP 2010|
|Keyword(s)||Unknown (Extra: Data sparsity, Hyperlinks, Latent semantics, Real-world datasets, Recommender algorithms, Wikipedia, Hypertext systems, Recommender systems, Semantics)|
|Article||BASE, CiteSeerX, Google Scholar|
|Web||Ask, Bing, Google (PDF), Yahoo!|
|Download and mirrors|
|Local copy||Not available|
|Remote mirror(s)||Not available|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of conference papers|
Using Wikipedia to alleviate data sparsity issues in Recommender Systems is a 2010 conference paper written in English by Loizou A., Dasmahapatra S. and published in Proceedings - 2010 5th International Workshop on Semantic Media Adaptation and Personalization, SMAP 2010.
This paper proposes that Wikipedia can effectively be used in order to lessen the negative effects of data sparsity on the accuracy of recommendations produced by Recommender Systems, provided that domain resources available for recommendation can successfully be mapped to Wikipedia articles. Under the assumption that hyperlinks between Wikipedia articles convey latent semantic relationships between the concepts they represent, we argue that by representing domain resources as a set of interconnected Wikipedia articles the volume of information available to a recommender algorithm increases, enabling it to improve its performance. The approach is evaluated using two real world datasets, giving positive results.
- This section requires expansion. Please, help!
Probably, this publication is cited by others, but there are no articles available for them in WikiPapers. Cited 1 time(s)