On-Device User Intent Prediction for Context and Sequence Aware Recommendation

Multidimensional Binary Search Trees Used for Associative Searching

Jon Louis Bentley. 1975 · 1975

Earlier work this paper cites.

String Comparator Metrics and Enhanced Decision Rules in the Fellegi-Sunter Model of Record Linkage. In Proceedings of the Section on Survey Research . 354–359

William E. Winkler. 1990 · 1990

Earlier work this paper cites.

A Guided Tour to Approximate String Matching

Gonzalo Navarro. 2001 · 2001

Earlier work this paper cites.

Using Temporal Data for Making Recommendations. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI’01) . Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 580–588

Andrew Zimdars, David Maxwell Chickering, and Christopher Meek. 2001 · 2001

Earlier work this paper cites.

Incorporating Contextual Information in Recommender Systems Using a Multidimensional Approach

Gediminas Adomavicius, Ramesh Sankaranarayanan, Shahana Sen, and Alexander Tuzhilin. 2005 · 2005

Earlier work this paper cites.

A Comparison of Personal Name Matching: Techniques and Practical Issues. In Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (ICDMW ’06) . IEEE Computer Society, Washington, DC, USA, 290–294

Peter Christen. 2006 · 2006

Earlier work this paper cites.

Matrix Factorization Techniques for Recommender Systems

Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009

Earlier work this paper cites.

Factorizing Personalized Markov Chains for Next-basket Recommendation. In Proceedings of the 19th International Conference on World Wide Web (WWW ’10) . ACM, New York, NY, USA, 811–820

Steffen Rendle, Christoph Freudenthaler, and Lars Schmidt-Thieme. 2010 · 2010

Cited alongside, same era.

Let’s Do It at My Place Instead?: Attitudinal and Behavioral Study of Privacy in Client-side Personalization. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’14) . ACM, New York, NY, USA, 81–90

Alfred Kobsa, Bart P. Knijnenburg, and Benjamin Livshits. 2014 · 2014

Cited alongside, same era.

Graph-based point-of-interest recommendation with geographical and temporal influences. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management . ACM, 659–668

Quan Yuan, Gao Cong, and Aixin Sun. 2014 · 2014

Cited alongside, same era.

Predicting The Next App That You Are Going To Use. In Proceedings of the Eighth ACM International Conference on Web Search and Data Mining (WSDM ’15) . ACM, New York, NY, USA, 285–294

Ricardo Baeza-Yates, Di Jiang, Fabrizio Silvestri, and Beverly Harrison. 2015 · 2015

Privacy for Recommender Systems: Tutorial Abstract. In Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys ’17) . ACM, New York, NY, USA, 394–395

Bart P. Knijnenburg and Shlomo Berkovsky. 2017 · 2017

Later among the works it cites.

An Experimental Evaluation of Point-of-interest Recommendation in Location-based Social Networks

Yiding Liu, Tuan-Anh Nguyen Pham, Gao Cong, and Quan Yuan. 2017 · 2017

Later among the works it cites.

Context-aware recommender systems in mobile environment: On the road of future research

Imen Ben Sassi, Sehl Mellouli, and Sadok Ben Yahia. 2017 · 2017

Later among the works it cites.

Third Party Tracking in the Mobile Ecosystem. In Proceedings of the 10th ACM Conference on Web Science (WebSci ’18) . ACM, New York, NY, USA, 23–31

Reuben Binns, Ulrik Lyngs, Max Van Kleek, Jun Zhao, Timothy Libert, and Nigel Shadbolt. 2018 · 2018

Later among the works it cites.

Sequence-Aware Recommender Systems

Massimo Quadrana, Paolo Cremonesi, and Dietmar Jannach. 2018 · 2018