Fetching the paper…
Reading the bibliography…
Virtual assistants, also known as intelligent conversational systems such as Google's Virtual Assistant and Apple's Siri, interact with human-like responses to users' queries and finish specific tasks.
Personalized conversational case-based recommendation
Mehmet H. Göker and Cynthia A. Thompson · 2000
Earlier work this paper cites.
Matrix factorization techniques for recommender systems
Yehuda Koren, Robert M. Bell, and Chris Volinsky · 2009
Earlier work this paper cites.
Probabilistic matrix tri-factorization
Jiho Yoo and Seungjin Choi · 2009
Earlier work this paper cites.
The youtube video recommendation system
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
Earlier work this paper cites.
Musicbox: Personalized music recommendation based on cubic analysis of social tags
Alexandros Nanopoulos, Dimitrios Rafailidis, Panagiotis Symeonidis, and Yannis Manolopoulos · 2010
Earlier work this paper cites.
On the evolution of critiquing recommenders
Lorraine McGinty and James Reilly · 2011
Earlier work this paper cites.
A personalized system for conversational recommendations
Mehmet H. Göker, Pat Langley, and Cynthia A. Thompson · 2011
Earlier work this paper cites.
Content-based recommender systems: State of the art and trends
Pasquale Lops, Marco de Gemmis, and Giovanni Semeraro · 2011
Earlier work this paper cites.
Collaborative topic modeling for recommending scientific articles
Chong Wang and David M. Blei · 2011
Earlier work this paper cites.
Hidden factors and hidden topics: understanding rating dimensions with review text
Julian J. McAuley and Jure Leskovec · 2013
Earlier work this paper cites.
The TFC model: Tensor factorization and tag clustering for item recommendation in social tagging systems
Dimitrios Rafailidis and Petros Daras · 2013
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean · 2013
Earlier work this paper cites.
Content-based tag propagation and tensor factorization for personalized item recommendation based on social tagging
Dimitrios Rafailidis, Apostolos Axenopoulos, Jonas Etzold, Stavroula Manolopoulou, and Petros Daras · 2014
Earlier work this paper cites.
Novelty and diversity enhancement and evaluation in recommender systems and information retrieval
Saúl Vargas · 2014
Earlier work this paper cites.
Modeling the dynamics of user preferences in coupled tensor factorization
Dimitrios Rafailidis and Alexandros Nanopoulos · 2014
Earlier work this paper cites.
A multi-view deep learning approach for cross domain user modeling in recommendation systems
Ali Mamdouh Elkahky, Yang Song, and Xiaodong He · 2015
Earlier work this paper cites.
Oriol Vinyals and Quoc V. Le · 2015
Earlier work this paper cites.
Evaluating recommender systems
Asela Gunawardana and Guy Shani · 2015
Earlier work this paper cites.
Repeat consumption recommendation based on users preference dynamics and side information
Dimitrios Rafailidis and Alexandros Nanopoulos · 2015
Earlier work this paper cites.
Improving top-n recommendation for cold-start users via cross-domain information
Nima Mirbakhsh and Charles X. Ling · 2015
Earlier work this paper cites.
Towards conversational recommender systems
Konstantina Christakopoulou, Filip Radlinski, and Katja Hofmann · 2016
Earlier work this paper cites.
The netflix recommender system: Algorithms, business value, and innovation
Carlos A. Gomez-Uribe and Neil Hunt · 2016
Earlier work this paper cites.
Joint collaborative ranking with social relationships in top-n recommendation
Dimitrios Rafailidis and Fabio Crestani · 2016
Cited alongside, same era.
Collaborative ranking with social relationships for top-n recommendations
Dimitrios Rafailidis and Fabio Crestani · 2016
Cited alongside, same era.
A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and Bill Dolan · 2016
Cited alongside, same era.
Tiancheng Zhao and Maxine Eskénazi · 2016
Cited alongside, same era.
Modeling users preference dynamics and side information in recommender systems
Dimitrios Rafailidis and Alexandros Nanopoulos · 2016
Cited alongside, same era.
Conversational recommender system
Yueming Sun and Yi Zhang · 2018
Closest in time.
Towards conversational search and recommendation: System ask, user respond
Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W. Bruce Croft · 2018
Closest in time.
A collaborative ranking model with multiple location-based similarities for venue suggestion
Mohammad Aliannejadi, Dimitrios Rafailidis, and Fabio Crestani · 2018
Closest in time.
[Online]. Available: https://www.drgdigital.com/
2018
Closest in time.
[Online]. Available: https://www.statista.com/statistics
2018
Closest in time.
[Online]. Available: https://www.techradar.com/
2018
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Top-n recommendation via joint cross-domain user clustering and similarity learning
Dimitrios Rafailidis and Fabio Crestani · 2016
Cited alongside, same era.
Pairwise preferences based matrix factorization and nearest neighbor recommendation techniques
Saikishore Kalloori, Francesco Ricci, and Marko Tkalcic · 2016
Cited alongside, same era.
A regularization method with inference of trust and distrust in recommender systems
Dimitrios Rafailidis and Fabio Crestani · 2017
Cited alongside, same era.
Learning to rank with trust and distrust in recommender systems
Dimitrios Rafailidis and Fabio Crestani · 2017
Cited alongside, same era.
Perspectives for evaluating conversational AI
Mahipal Jadeja and Neelanshi Varia · 2017
Cited alongside, same era.
A theoretical framework for conversational search
Filip Radlinski and Nick Craswell · 2017
Cited alongside, same era.
Attentive memory networks: Efficient machine reading for conversational search
Tom Kenter and Maarten de Rijke · 2017
Cited alongside, same era.
2018
Closest in time.
[Online]. Available: http://www.internetlivestats.com/internet-users/
2018
Closest in time.
Pocket skills: A conversational mobile web app to support dialectical behavioral therapy
Jessica Schroeder, Chelsey Wilkes, Kael Rowan, Arturo Toledo, Ann Paradiso, Mary Czerwinski, Gloria Mark, and Marsha M. Linehan · 2018
Closest in time.
Response ranking with deep matching networks and external knowledge in information-seeking conversation systems
Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Jun Huang, and Haiqing Chen · 2018
Closest in time.
On the robustness and discriminative power of information retrieval metrics for top-n recommendation
Daniel Valcarce, Alejandro Bellogín, Javier Parapar, and Pablo Castells · 2018
Closest in time.
Transfer learning for context-aware question matching in information-seeking conversations in e-commerce
Minghui Qiu, Liu Yang, Feng Ji, Wei Zhou, Jun Huang, Haiqing Chen, W. Bruce Croft, and Wei Lin · 2018
Closest in time.
GeoDCF: Deep collaborative filtering with multifaceted contextual information in location-based social networks
Dimitrios Rafailidis and Fabio Crestani · 2018
Closest in time.
Friend recommendation in location-based social networks via deep pairwise learning
Dimitrios Rafailidis and Fabio Crestani · 2018
Closest in time.
A multi-latent transition model for evolving preferences in recommender systems
Dimitrios Rafailidis · 2018
Closest in time.
Explore, exploit, and explain: personalizing explainable recommendations with bandits
James McInerney, Benjamin Lacker, Samantha Hansen, Karl Higley, Hugues Bouchard, Alois Gruson, and Rishabh Mehrotra · 2018
Closest in time.
Eliciting pairwise preferences in recommender systems
Saikishore Kalloori, Francesco Ricci, and Rosella Gennari · 2018
Closest in time.
[Online]. Available: https://wit.ai/
2018
Closest in time.
Measuring semantic coherence of a conversation
Svitlana Vakulenko, Maarten de Rijke, Michael Cochez, Vadim Savenkov, and Axel Polleres · 2018
Closest in time.
Online learning for non-stationary A/B tests
Andrés Muñoz Medina, Sergei Vassilvitskii, and Dong Yin · 2018
Closest in time.
On cross-domain transfer in venue recommendation
Jarana Manotumruksa, Dimitrios Rafailidis, Craig Macdonald, and Iadh Ounis · 2019
Closest in time.