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4 results on '"Ren, Yongli"'

1. Relation Embedding for Personalised Translation-Based POI Recommendation

Author

Wang, Xianjing, Salim, Flora D., Ren, Yongli, Koniusz, Piotr, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Lauw, Hady W., editor, Wong, Raymond Chi-Wing, editor, Ntoulas, Alexandros, editor, Lim, Ee-Peng, editor, Ng, See-Kiong, editor, and Pan, Sinno Jialin, editor

Published
2020
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2. A Probabilistic Graph-Based Method to Improve Recommender System Accuracy

Author

Joorabloo, Nima, Jalili, Mahdi, Ren, Yongli, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Macintyre, John, editor, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, and Jayne, Chrisina, editor

Published
2019
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3. A survey of recommendation techniques based on offline data processing.

Author

Ren, Yongli, Li, Gang, and Zhou, Wanlei

Subjects
RECOMMENDER systems, ELECTRONIC data processing, BIG data, BENCHMARKING (Management)
Abstract

Recommendations based on offline data processing has attracted increasing attention from both research communities and IT industries. The recommendation techniques could be used to explore huge volumes of data, identify the items that users probably like, translate the research results into real-world applications and so on. This paper surveys the recent progress in the research of recommendations based on offline data processing, with emphasis on new techniques (such as temporal recommendation, graph-based recommendation and trust-based recommendation), new features (such as serendipitous recommendation) and new research issues (such as tag recommendation and group recommendation). We also provide an extensive review of evaluation measurements, benchmark data sets and available open source tools. Finally, we outline some existing challenges for future research. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Published
2015
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