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Leveraging geographical metadata to improve search over social media

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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    L. Hong, A. Ahmed, S. Gurumurthy, A. Smola, and K. Tsioutsiouliklis. Discovering geographical topics in the twitter stream. In Proceedings of WWW'12, pages 769--778, 2012.
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    V. Lavrenko and W. B. Croft. Relevance-based language models. In Proceedings of ACM SIGIR'01, pages 120--127, 2001.
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    X. Yi and J. Allan. A comparative study of utilizing topic models for information retrieval. In Proceedings of ECIR'09, pages 29--41, 2009.
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    Cited By

    View all
    • (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
    • (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
    • (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
    • Show More Cited By

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    1. Leveraging geographical metadata to improve search over social media

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      Published In

      cover image ACM Other conferences
      WWW '13 Companion: Proceedings of the 22nd International Conference on World Wide Web
      May 2013
      1636 pages
      ISBN:9781450320382
      DOI:10.1145/2487788
      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.

      Sponsors

      • NICBR: Nucleo de Informatcao e Coordenacao do Ponto BR
      • CGIBR: Comite Gestor da Internet no Brazil

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      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 13 May 2013

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      Author Tags

      1. language models
      2. microblog retrieval
      3. probabilistic retrieval models
      4. social media
      5. topic models

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      • Poster

      Conference

      WWW '13
      Sponsor:
      • NICBR
      • CGIBR
      WWW '13: 22nd International World Wide Web Conference
      May 13 - 17, 2013
      Rio de Janeiro, Brazil

      Acceptance Rates

      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

      View all
      • (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
      • (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
      • (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
      • (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
      • (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
      • (2016)TopPRFACM Transactions on Information Systems10.1145/295623434:4(1-36)Online publication date: 29-Aug-2016
      • (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
      • (2015)Geographical Latent Variable Models for Microblog RetrievalAdvances in Information Retrieval10.1007/978-3-319-16354-3_70(635-647)Online publication date: 2015
      • (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

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