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Leveraging geographical metadata to improve search over social media

Authors:

Alexander Kotov,

Yu Wang,

Eugene AgichteinAuthors Info & Claims

WWW '13 Companion: Proceedings of the 22nd International Conference on World Wide Web

Pages 151 - 152

https://doi.org/10.1145/2487788.2487861

Published: 13 May 2013 Publication History

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Abstract

We propose the methods for document, query and relevance model expansion that leverage geographical metadata provided by social media. In particular, we propose a geographically-aware extension of the LDA topic model and utilize the resulting topics and language models in our expansion methods. The proposed approach has been experimentally evaluated over a large sample of Twitter, demonstrating significant improvements in search accuracy over traditional (geographically-unaware) retrieval models.

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Cited By

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Balaneshin-kordan SKotov AChang YZhai CLiu YMaarek Y(2018)Deep Neural Architecture for Multi-Modal Retrieval based on Joint Embedding Space for Text and ImagesProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159735(28-36)Online publication date: 2-Feb-2018
https://dl.acm.org/doi/10.1145/3159652.3159735
Albishre KLi YXu Y(2018)Query-Based Automatic Training Set Selection for Microblog RetrievalAdvances in Knowledge Discovery and Data Mining10.1007/978-3-319-93037-4_26(325-336)Online publication date: 20-Jun-2018
https://doi.org/10.1007/978-3-319-93037-4_26
Alkhodair SFung BRahman OHung P(2018)Improving interpretations of topic modeling in microblogsJournal of the Association for Information Science and Technology10.1002/asi.2398069:4(528-540)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1002/asi.23980
Show More Cited By

Index Terms

Leveraging geographical metadata to improve search over social media
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Information

Published In

WWW '13 Companion: Proceedings of the 22nd International Conference on World Wide Web

May 2013

1636 pages

ISBN:9781450320382

DOI:10.1145/2487788

General Chairs:
Daniel Schwabe
PUC-Rio - Brazil
,
Virgílio Almeida
UFMG - Brazil
,
Hartmut Glaser
CGI.br - Brazil
,
Program Chairs:
Ricardo Baeza-Yates
Yahoo! Labs - Spain & Chile
,
Sue Moon
KAIST - South Korea

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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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

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Published: 13 May 2013

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WWW '13

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NICBR
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WWW '13: 22nd International World Wide Web Conference

May 13 - 17, 2013

Rio de Janeiro, Brazil

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WWW '13 Companion Paper Acceptance Rate 831 of 1,250 submissions, 66%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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Balaneshin-kordan SKotov AChang YZhai CLiu YMaarek Y(2018)Deep Neural Architecture for Multi-Modal Retrieval based on Joint Embedding Space for Text and ImagesProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159735(28-36)Online publication date: 2-Feb-2018
https://dl.acm.org/doi/10.1145/3159652.3159735
Albishre KLi YXu Y(2018)Query-Based Automatic Training Set Selection for Microblog RetrievalAdvances in Knowledge Discovery and Data Mining10.1007/978-3-319-93037-4_26(325-336)Online publication date: 20-Jun-2018
https://doi.org/10.1007/978-3-319-93037-4_26
Alkhodair SFung BRahman OHung P(2018)Improving interpretations of topic modeling in microblogsJournal of the Association for Information Science and Technology10.1002/asi.2398069:4(528-540)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1002/asi.23980
Rakesh VJadhav NKotov AReddy Cde Rijke MShokouhi MTomkins AZhang M(2017)Probabilistic Social Sequential Model for Tour RecommendationProceedings of the Tenth ACM International Conference on Web Search and Data Mining10.1145/3018661.3018711(631-640)Online publication date: 2-Feb-2017
https://dl.acm.org/doi/10.1145/3018661.3018711
Balaneshin-kordan SKotov ACarterette BFang HLalmas MNie J(2016)A Study of Document Expansion using Translation Models and Dimensionality Reduction MethodsProceedings of the 2016 ACM International Conference on the Theory of Information Retrieval10.1145/2970398.2970439(233-236)Online publication date: 12-Sep-2016
https://dl.acm.org/doi/10.1145/2970398.2970439
Miao JHuang JZhao J(2016)TopPRFACM Transactions on Information Systems10.1145/295623434:4(1-36)Online publication date: 29-Aug-2016
https://dl.acm.org/doi/10.1145/2956234
Yang ZKotov AMohan ALu SBaeza-Yates RLalmas MMoffat ARibeiro-Neto B(2015)Parametric and Non-parametric User-aware Sentiment Topic ModelsProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/2766462.2767758(413-422)Online publication date: 9-Aug-2015
https://dl.acm.org/doi/10.1145/2766462.2767758
Kotov ARakesh VAgichtein EReddy C(2015)Geographical Latent Variable Models for Microblog RetrievalAdvances in Information Retrieval10.1007/978-3-319-16354-3_70(635-647)Online publication date: 2015
https://doi.org/10.1007/978-3-319-16354-3_70
Kotov AAgichtein EHe QIyengar ANejdl WPei JRastogi R(2013)The importance of being socially-savvyProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2507892(1905-1908)Online publication date: 27-Oct-2013
https://dl.acm.org/doi/10.1145/2505515.2507892

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Capturing Changes in Social Media Content: A Multiple Latent Changepoint Topic Model

Uses and gratifications of social networking sites for bridging and bonding social capital

Aggregated topic models for increasing social media topic coherence

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