A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users

no code implementations • 20 Jun 2017 • Wang Hao, Fu Yanmei, Wang Qinyong, Yin Hongzhi, Du Changying, Xiong Hui

In this paper, we propose a latent probabilistic generative model called LSARS to mimic the decision-making process of users' check-in activities both in home-town and out-of-town scenarios by adapting to user interest drift and crowd sentiments, which can learn location-aware and sentiment-aware individual interests from the contents of spatial items and user reviews.

Decision Making Recommendation Systems

Structural Analysis of User Choices for Mobile App Recommendation

no code implementations • 25 May 2016 • Liu Bin, Wu Yao, Gong Neil Zhenqiang, Wu Junjie, Xiong Hui, Ester Martin

While there are a variety of approaches for mobile app recommendations, these approaches do not have a focus on dealing with these opportunities and challenges.