Can Virtual Assistants Produce Recommendations?

Author:

Rafailidis Dimitrios1,Manolopoulos Yannis2

Affiliation:

1. Maastricht University, Maastricht, The Netherlands

2. Aristotle University of Thessaloniki, Thessaloniki, Greece

Publisher

ACM Press

Reference49 articles.

1. Mohammad Aliannejadi, Dimitrios Rafailidis, and Fabio Crestani. 2017. Personalized Keyword Boosting for Venue Suggestion Based on Multiple LBSNs. In Proceedings of 39th European Conference on IR Research, ECIR 2017, Aberdeen, UK. 291--303.

2. Tomas Mikolov andIlya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. In Proceedings 27th Annual Conference on Neural Information Processing Systems. Lake Tahoe, NV, 3111--3119.

3. Rocío Cañamares and Pablo Castells. 2018. Should I Follow the Crowd?: A Probabilistic Analysis of the Effectiveness of Popularity in Recommender Systems. In Proceedings 41st ACM International Conference on Research & Development in Information Retrieval (SIGIR). Ann Arbor, MI, 415--424.

4. James Davidson, Benjamin Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu He, Mike Lambert, Blake Livingston, and Dasarathi Sampath. 2010. The YouTube Video Recommendation System. In Proceedings 4th ACM Conference on Recommender Systems (RecSys). Barcelona, Spain, 293--296.

5. Bhuwan Dhingra, Lihong Li, Xiujun Li, Jianfeng Gao, Yun-Nung Chen, Faisal Ahmed, and Li Deng. 2017. Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access. In Proceedings 55th Annual Meeting of the Association for Computational Linguistics (ACL), Vol. I. Vancouver, Canada, 484--495.

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