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RECSYS
2015
ACM

Exploiting Geo-Spatial Preference for Personalized Expert Recommendation

4 years 3 months ago
Exploiting Geo-Spatial Preference for Personalized Expert Recommendation
Experts are important for providing reliable and authoritative information and opinion, as well as for improving online reviews and services. While considerable previous research has focused on finding topical experts with broad appeal – e.g., top Java developers, best lawyers in Texas – we tackle the problem of personalized expert recommendation, to identify experts who have special personal appeal and importance to users. One of the key insights motivating our approach is to leverage the geo-spatial preferences of users and the variation of these preferences across different regions, topics, and social communities. Through a fine-grained GPS-tagged social media trace, we characterize these geo-spatial preferences for personalized experts, and integrate these preferences into a matrix factorization-based personalized expert recommender. Through extensive experiments, we find that the proposed approach can improve the quality of recommendation by 24% in precision compared to se...
Haokai Lu, James Caverlee
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where RECSYS
Authors Haokai Lu, James Caverlee
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