invited-talk

The Role of User Location in Personalized Search and Recommendation

Author:

Ido GuyAuthors Info & Claims

RecSys '15: Proceedings of the 9th ACM Conference on Recommender Systems

Page 236

https://doi.org/10.1145/2792838.2799502

Published: 16 September 2015 Publication History

Abstract

With mobile devices, users no longer access the web from specific locations, but virtually from anywhere. How does this affect our ability to provide personalized information for users' In this talk, I will discuss the influence of location activity on users' information needs and how a better understanding of these needs can help enhance web applications in which personalization plays a central role.

References

[1]

Guy, I., Avraham, U., Carmel, D., Ur, S., Jacovi, M., and Ronen, I. 2013. Mining expertise and interests from social media. Proc. WWW '13, 515--526.

Digital Library

[2]

Guy, I., Hashavit, A., and Corem, Y. 2015. Games for crowds: A crowdsourcing game platform for the enterprise. Proc. CSCW '15, 1860--1871.

Digital Library

[3]

Guy, I., Levin, R., Daniel, T., and Bolshinsky, E. 2015. Islands in the Stream: A study of item recommendation within an enterprise social stream. Proc. SIGIR '15.

Digital Library

[4]

Guy, I., Perer, A., Daniel, T., Greenshpan, O., and Turbahn, I. 2011. Guess who? Enriching the social graph through a crowdsourcing game. Proc. CHI '11, 1373--1382.

Digital Library

[5]

Guy, I., Ronen, I., and Raviv, A. 2011. Personalized activity streams: Sifting through the "river of news". Proc. RecSys '11, 181--188.

Digital Library

[6]

Guy, I., Ronen, I., and Wilcox, E. 2009. Do you know? Recommending people to invite into your social network. Proc. IUI '09, 77--86.

Digital Library

[7]

Guy, I., Steier, T., Barnea, M., Ronen, I., and Daniel, T. 2012. Swimming against the streamz: Search and analytics over the enterprise activity stream. Proc. CIKM '12, 1587--1591.

Digital Library

[8]

Guy, I., Ur, S., Ronen, I., Perer, A., and Jacovi, M. 2011. Do you want to know? Recommending strangers in the enterprise. Proc. CSCW '11, 285--294.

Digital Library

[9]

Guy, I., Ur, S., Ronen, I., Weber, S., and Oral, T. 2012. Best faces forward: A large-scale study of people search in the enterprise. Proc. CHI '12, 1775--1784.

Digital Library

[10]

Guy, I., Zwerdling, N., Carmel, D., Ronen, I., Uziel, E., Yogev, S., and Ofek-Koifman, S. 2009. Personalized recommendation of social software items based on social relations. Proc. RecSys '09, 53--60.

Digital Library

[11]

Guy, I., Zwerdling, N., Ronen, I., Carmel, D., and Uziel, E. 2010. Social media recommendation based on people and tags. Proc. SIGIR '10, 194--201.

Digital Library

[12]

Jacovi, M., Guy, I., Kremer-Davidson, S., Porat, S., and Aizenbud-Reshef, N. 2014. The perception of others: Inferring reputation from social media in the enterprise. Proc. CSCW '14, 756--766.

Digital Library

[13]

Jacovi, M., Guy, I., Ronen, I., Perer, A., Uziel, E., and Maslenko, M. 2011. Digital traces of interest: Deriving interest relationships from social media interactions. Proc. ECSCW '11, 21--40.

[14]

Kravi, E., Agichtein, E., Guy, I., Kanza, Y., Mejer, A., and Pelleg, D. 2015. Searcher in a strange land: Understanding web search from familiar and unfamiliar locations. Proc. SIGIR '15.

Digital Library

[15]

Perer, A., Guy, I., Uziel, E., Ronen, I., and Jacovi, M. 2011. Visual social network analytics for relationship discovery in the enterprise. Proc. VAST '11, 71--79.

[16]

Ronen, I., Guy, I., Kravi, E., and Barnea, M. 2014. Recommending social media content to community owners. Proc. SIGIR '14, 243--252.

Digital Library

[17]

Yogev, A., Guy, I., Ronen, I., Zwerdling, N., and Barnea, M. 2015. Social media-based expertise evidence. Proc. ECSCW '15.

Cited By

Davtalab MAlesheikh A(2020)A POI recommendation approach integrating social spatio-temporal information into probabilistic matrix factorizationKnowledge and Information Systems10.1007/s10115-020-01509-5Online publication date: 12-Sep-2020
https://doi.org/10.1007/s10115-020-01509-5
Hashemi SKamps JBielikova MHerder ECena FDesmarais M(2017)Where To Go Next?Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization10.1145/3079628.3079687(50-58)Online publication date: 9-Jul-2017
https://dl.acm.org/doi/10.1145/3079628.3079687
Hashemi SKamps JNordlie RPharo NFreund LLarsen BRussel D(2017)Skip or StayProceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval10.1145/3020165.3022160(389-392)Online publication date: 7-Mar-2017
https://dl.acm.org/doi/10.1145/3020165.3022160

Index Terms

The Role of User Location in Personalized Search and Recommendation
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Information & Contributors

Information

Published In

cover image ACM Conferences

RecSys '15: Proceedings of the 9th ACM Conference on Recommender Systems

September 2015

414 pages

ISBN:9781450336925

DOI:10.1145/2792838

General Chairs:
Hannes Werthner
TU Wien, Austria
,
Markus Zanker
Alpen-Adria-Universität Klagenfurt, Austria
,
Program Chairs:
Jennifer Golbeck
University of Maryland, USA
,
Giovanni Semeraro
University of Bari Aldo Moro, Italy

Copyright © 2015 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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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 September 2015

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Invited-talk

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RecSys '15

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SIGCHI

RecSys '15: Ninth ACM Conference on Recommender Systems

September 16 - 20, 2015

Vienna, Austria

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RecSys '15 Paper Acceptance Rate 28 of 131 submissions, 21%;

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

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Cited By

Davtalab MAlesheikh A(2020)A POI recommendation approach integrating social spatio-temporal information into probabilistic matrix factorizationKnowledge and Information Systems10.1007/s10115-020-01509-5Online publication date: 12-Sep-2020
https://doi.org/10.1007/s10115-020-01509-5
Hashemi SKamps JBielikova MHerder ECena FDesmarais M(2017)Where To Go Next?Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization10.1145/3079628.3079687(50-58)Online publication date: 9-Jul-2017
https://dl.acm.org/doi/10.1145/3079628.3079687
Hashemi SKamps JNordlie RPharo NFreund LLarsen BRussel D(2017)Skip or StayProceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval10.1145/3020165.3022160(389-392)Online publication date: 7-Mar-2017
https://dl.acm.org/doi/10.1145/3020165.3022160

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