extended-abstract

Workshop on context-aware recommender systems

Authors:

Gediminas Adomavicius,

Konstantin Bauman,

Bamshad Mobasher,

Francesco Ricci,

Alexander Tuzhilin,

Moshe UngerAuthors Info & Claims

RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems

Pages 548 - 549

https://doi.org/10.1145/3298689.3346954

Published: 10 September 2019 Publication History

Abstract

Contextual information has been widely recognized as an important modeling dimension both in social sciences and in computing. In particular, the role of context has been recognized in enhancing recommendation results and retrieval performance. While a substantial amount of existing research has focused context-aware recommender systems (CARS), many interesting problems remain under-explored. The CARS 2019 workshop provides a venue for presenting and discussing approaches for next generation of CARS and application domains that may require a variety of dimensions of contexts and cope with its dynamic properties.

References

[1]

Gediminas Adomavicius, Linas Baltrunas, Ernesto William De Luca, Tim Hussein, and Alexander Tuzhilin. 2012. 4th workshop on context-aware recommender systems (CARS 2012). In 6th ACM Conference on Recommender Systems, RecSys 2012.

Digital Library

[2]

Gediminas Adomavicius, Linas Baltrunas, Tim Hussein, Francesco Ricci, and Alexander Tuzhilin. 2011. 3rd workshop on context-aware recommender systems (CARS 2011). In CEUR Workshop Proceedings, Vol. 791.

Digital Library

[3]

Gediminas Adomavicius and Francesco Ricci. 2009. RecSys' 09 workshop 3: workshop on context-aware recommender systems (CARS-2009). In Proceedings of the third ACM conference on Recommender systems. ACM, 423--424.

Digital Library

[4]

Gediminas Adomavicius and Alexander Tuzhilin. 2005. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering 17, 6 (2005), 734--749.

Digital Library

[5]

Gediminas Adomavicius and Alexander Tuzhilin. 2015. Context-aware recommender systems. In Recommender systems handbook. Springer, 191--226.

[6]

Gediminas Adomavicius, Alexander Tuzhilin, Shlomo Berkovsky, Ernesto W De Luca, and Alan Said. 2010. Context-aware recommender systems: research workshop and movie recommendation challenge. ACM RecSys2010 (2010), 26--30.

Digital Library

[7]

Mehdi Hosseinzadeh Aghdam, Negar Hariri, Bamshad Mobasher, and Robin D Burke. 2015. Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models. RecSys 15 (2015), 241--244.

Digital Library

[8]

Konstantin Bauman and Alexander Tuzhilin. 2014. Discovering Contextual Information from User Reviews for Recommendation Purposes. In Content-Based Recommender Systems (CBRecSys).

[9]

Matthias Böhmer, Ernesto W De Luca, Alan Said, and Jaime Teevan. 2013. 3rd workshop on context-awareness in retrieval and recommendation. In Proceedings of the sixth ACM international conference on Web search and data mining. ACM, 789--790.

Digital Library

[10]

Ernesto William De Luca, Matthias Böhmer, Alan Said, and Ed Chi. 2012. 2nd workshop on context-awareness in retrieval and recommendation:(carr 2012). In Proceedings of the 2012 ACM international conference on Intelligent User Interfaces. ACM, 409--412.

Digital Library

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Ernesto William De Luca, Alan Said, Matthias Böhmer, and Florian Michahelles. 2011. Workshop on context-awareness in retrieval and recommendation. In Proceedings of the 16th international conference on Intelligent user interfaces. ACM, 471--472.

[12]

Ernesto William De Luca, Alan Said, Fabio Crestani, and David Elsweiler. 2015. 5th Workshop on Context-Awareness in Retrieval and Recommendation. In European Conference on Information Retrieval. Springer, 830--833.

[13]

Negar Hariri, Bamshad Mobasher, and Robin Burke. 2012. Context-aware music recommendation based on latenttopic sequential patterns. In Proceedings of the sixth ACM conference on Recommender systems. ACM, 131--138.

Digital Library

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David Massimo and Francesco Ricci. 2018. Harnessing a generalised user behaviour model for next-POI recommendation. In Proceedings of the 12th ACM Conference on Recommender Systems, RecSys 2018, Vancouver, BC, Canada, October 2--7, 2018. 402--406.

Digital Library

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Massimo Quadrana, Paolo Cremonesi, and Dietmar Jannach. 2018. Sequence-Aware Recommender Systems. ACM Comput. Surv. 51, 4 (2018), 66:1--66:36.

Digital Library

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Alan Said, Ernesto William De Luca, Daniele Quercia, and Matthias Böhmer. 2014. 4 th Workshop on Context-Awareness in Retrieval and Recommendation. In European Conference on Information Retrieval. Springer, 802--805.

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Elena Smirnova and Flavian Vasile. 2017. Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks. arXiv preprint arXiv: 1706.07684 (2017).

[18]

Moshe Unger, Ariel Bar, Bracha Shapira, and Lior Rokach. 2016. Towards latent context-aware recommendation systems. Knowledge-Based Systems 104 (2016), 165--178.

Digital Library

Cited By

A VS GA VS G(2024)IntroductionA Context Aware Decision-Making Algorithm for Human-Centric Analytics: Algorithm Development and Use Cases for Health Informatics System10.2174/9789815305968124010003(1-22)Online publication date: 15-Oct-2024
https://doi.org/10.2174/9789815305968124010003

Index Terms

Workshop on context-aware recommender systems
1. Computing methodologies
  1. Machine learning
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems
  2. Information systems applications
    1. Data mining

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Information & Contributors

Information

Published In

cover image ACM Other conferences

RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems

September 2019

635 pages

ISBN:9781450362436

DOI:10.1145/3298689

General Chairs:
Toine Bogers
Aalborg University Copenhagen, Denmark
,
Alan Said
University of Gothenburg, Sweden
,
Program Chairs:
Peter Brusilovsky
University of Pittsburgh
,
Domonkos Tikk
Gravity R&D, Hungary

Copyright © 2019 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 September 2019

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Conference

RecSys '19

RecSys '19: Thirteenth ACM Conference on Recommender Systems

September 16 - 20, 2019

Copenhagen, Denmark

Acceptance Rates

RecSys '19 Paper Acceptance Rate 36 of 189 submissions, 19%;

Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Cited By

A VS GA VS G(2024)IntroductionA Context Aware Decision-Making Algorithm for Human-Centric Analytics: Algorithm Development and Use Cases for Health Informatics System10.2174/9789815305968124010003(1-22)Online publication date: 15-Oct-2024
https://doi.org/10.2174/9789815305968124010003

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