Neural Serendipity Recommendation

Recommender systems have been playing an important role in providing personalized information to users. However, there is always a trade-off between accuracy and novelty in recommender systems. Usu...

[1]  Tat-Seng Chua,et al.  Fast Matrix Factorization for Online Recommendation with Implicit Feedback , 2016, SIGIR.

[2]  Hui Xiong,et al.  Exploiting Temporal and Social Factors for B2B Marketing Campaign Recommendations , 2015, 2015 IEEE International Conference on Data Mining.

[3]  Xiaoyu Du,et al.  Adversarial Personalized Ranking for Recommendation , 2018, SIGIR.

[4]  Bin Guo,et al.  Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints , 2016, IEEE Transactions on Human-Machine Systems.

[5]  Hui Xiong,et al.  A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users , 2017, KDD.

[6]  Georg Lausen,et al.  Music recommenders based on hybrid techniques and serendipity , 2014, Web Intell. Agent Syst..

[7]  Zhan Xu,et al.  A New Information Theory-Based Serendipitous Algorithm Design , 2017, HCI.

[8]  Hui Xiong,et al.  Mobile app recommendations with security and privacy awareness , 2014, KDD.

[9]  Hui Xiong,et al.  NeuO: Exploiting the sentimental bias between ratings and reviews with neural networks , 2019, Neural Networks.

[10]  Shuaiqiang Wang,et al.  A survey of serendipity in recommender systems , 2016, Knowl. Based Syst..

[11]  Angshul Majumdar,et al.  Balancing accuracy and diversity in recommendations using matrix completion framework , 2017, Knowl. Based Syst..

[12]  Huanbo Luan,et al.  Discrete Collaborative Filtering , 2016, SIGIR.

[13]  Xing Xie,et al.  Representation learning via Dual-Autoencoder for recommendation , 2017, Neural Networks.

[14]  En Wang,et al.  Improving Existing Collaborative Filtering Recommendations via Serendipity-Based Algorithm , 2018, IEEE Transactions on Multimedia.

[15]  Hui Xiong,et al.  Learning to Recommend Accurate and Diverse Items , 2017, WWW.

[16]  Tat-Seng Chua,et al.  Neural Collaborative Filtering , 2017, WWW.

[17]  Hui Xiong,et al.  Unified Point-of-Interest Recommendation with Temporal Interval Assessment , 2016, KDD.

[18]  Chun Chen,et al.  Improving Collaborative Recommendation via User-Item Subgroups , 2016, IEEE Transactions on Knowledge and Data Engineering.

[19]  Hanghang Tong,et al.  RaPare: A Generic Strategy for Cold-Start Rating Prediction Problem , 2017, IEEE Transactions on Knowledge and Data Engineering.

[20]  Wenyu Zhang,et al.  An Approach for Building Efficient and Accurate Social Recommender Systems Using Individual Relationship Networks , 2017, IEEE Transactions on Knowledge and Data Engineering.

[21]  Tao Mei,et al.  Shop-Type Recommendation Leveraging the Data from Social Media and Location-Based Services , 2016, ACM Trans. Knowl. Discov. Data.

[22]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[23]  Katrien Verbert,et al.  Interactive recommender systems: A survey of the state of the art and future research challenges and opportunities , 2016, Expert Syst. Appl..

[24]  Hui Xiong,et al.  Multi-source Information Fusion for Personalized Restaurant Recommendation , 2015, SIGIR.

[25]  J. Bobadilla,et al.  Recommender systems survey , 2013, Knowl. Based Syst..

[26]  Dokyun Lee,et al.  When do Recommender Systems Work the Best?: The Moderating Effects of Product Attributes and Consumer Reviews on Recommender Performance , 2016, WWW.

[27]  Donald F. Specht,et al.  Probabilistic neural networks , 1990, Neural Networks.

[28]  HeChen,et al.  Interactive recommender systems , 2016 .

[29]  Jaana Kekäläinen,et al.  Cumulated gain-based evaluation of IR techniques , 2002, TOIS.

[30]  CARLOS A. GOMEZ-URIBE,et al.  The Netflix Recommender System , 2015, ACM Trans. Manag. Inf. Syst..

[31]  Sean M. McNee,et al.  Improving recommendation lists through topic diversification , 2005, WWW '05.

[32]  Dongwon Lee,et al.  “Told you i didn't like it”: Exploiting uninteresting items for effective collaborative filtering , 2016, 2016 IEEE 32nd International Conference on Data Engineering (ICDE).

[33]  Shuaiqiang Wang,et al.  Challenges of Serendipity in Recommender Systems , 2016, WEBIST.

[34]  Liu Yiqun,et al.  Learning and Transferring Social and Item Visibilities for Personalized Recommendation , 2017, CIKM.

[35]  Fillia Makedon,et al.  Using singular value decomposition approximation for collaborative filtering , 2005, Seventh IEEE International Conference on E-Commerce Technology (CEC'05).