H
Hui Fang
Researcher at Shanghai University of Finance and Economics
Publications - 51
Citations - 1361
Hui Fang is an academic researcher from Shanghai University of Finance and Economics. The author has contributed to research in topics: Recommender system & Computer science. The author has an hindex of 16, co-authored 40 publications receiving 883 citations. Previous affiliations of Hui Fang include Amazon.com & Nanyang Technological University.
Papers
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Proceedings Article
TopicMF: simultaneously exploiting ratings and reviews for recommendation
TL;DR: Experimental results show the superiority of the proposed novel matrix factorization model (called TopicMF) over the state-of-the-art models, demonstrating its effectiveness for recommendation tasks.
Journal ArticleDOI
Research commentary on recommendations with side information: A survey and research directions
TL;DR: A comprehensive and systematic survey of the recent research on recommender systems with side information can be found in this paper, where a number of recommendation algorithms have been proposed to leverage side information of users or items, demonstrating a high degree of effectiveness in improving recommendation performance.
Proceedings ArticleDOI
Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison
TL;DR: This paper systematically review 85 recommendation papers published at eight top-tier conferences and creates benchmarks with standardized procedures and provides the performance of seven well-tuned state-of-the-arts across six metrics on six widely-used datasets as a reference for later study.
Posted Content
Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
TL;DR: This survey illustrates the concept of sequential recommendation, proposes a categorization of existing algorithms in terms of three types of behavioral sequence, and summarizes the key factors affecting the performance of DL-based models and conducts corresponding evaluations to demonstrate the effects of these factors.
Journal ArticleDOI
Towards effective online review systems in the Chinese context: A cross-cultural empirical study
TL;DR: The impact of online reviews on product sales in the Chinese context is investigated, and it is shown that directly copying the ideas of successful online review systems in the USA will deteriorate the effectiveness of the systems in China.