Enhancing Precision of Markov-based recommenders Using Location Information

TitleEnhancing Precision of Markov-based recommenders Using Location Information
Publication TypeConference Paper
Year of Publication2014
AuthorsJalili, M., and H. R. Rabiee
Conference NameInternational Workshop on Big Data Search and Mining
Date Published09/2014
Conference LocationDelhi, India
Accession Number14779098
KeywordsCollaborative Filtering
AbstractRecommender systems are a real example of human computer interaction systems that both consumer/user and seller/service-provider benefit from it. Different techniques have been published in order to improve the quality of these systems. One of the approaches is using context information such as location of users or items. Most of the location-aware recommender systems utilize users’ location to improve memory-based collaborative filtering techniques. However, our proposed method is based on items’ location and utilizes a Markov-based approach which can be easily applied to implicit datasets. The main application of this technique is in datasets containing the location of items. Experimental results on real dataset show that the performance of the proposed method is much better than the classic CF methods.
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DOI<a href="http://dx.doi.org/10.1109/ICACCI.2014.6968579&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;