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Sopra: a new social personalized ranking function for improving web search

Published: 28 July 2013 Publication History

Abstract

We present in this paper a contribution to IR modeling by proposing a new ranking function called SoPRa that considers the social dimension of the Web. This social dimension is any social information that surrounds documents along with the social context of users. Currently, our approach relies on folksonomies for extracting these social contexts, but it can be extended to use any social meta-data, e.g. comments, ratings, tweets, etc. The evaluation performed on our approach shows its benefits for personalized search.

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Cited By

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  • (2023)Research in Collaborative Tagging Applications: Choosing the Right DatasetVAWKUM Transactions on Computer Sciences10.21015/vtcs.v11i1.130511:1(01-25)Online publication date: 5-Mar-2023
  • (2023)Personalized Query Expansion with Contextual Word EmbeddingsACM Transactions on Information Systems10.1145/362498842:2(1-35)Online publication date: 20-Sep-2023
  • (2022)A Multi-Domain Benchmark for Personalized Search EvaluationProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557536(3822-3827)Online publication date: 17-Oct-2022
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    cover image ACM Conferences
    SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
    July 2013
    1188 pages
    ISBN:9781450320344
    DOI:10.1145/2484028
    Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 28 July 2013

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    Author Tags

    1. information retrieval
    2. social networks

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    SIGIR '13 Paper Acceptance Rate 73 of 366 submissions, 20%;
    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    View all
    • (2023)Research in Collaborative Tagging Applications: Choosing the Right DatasetVAWKUM Transactions on Computer Sciences10.21015/vtcs.v11i1.130511:1(01-25)Online publication date: 5-Mar-2023
    • (2023)Personalized Query Expansion with Contextual Word EmbeddingsACM Transactions on Information Systems10.1145/362498842:2(1-35)Online publication date: 20-Sep-2023
    • (2022)A Multi-Domain Benchmark for Personalized Search EvaluationProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557536(3822-3827)Online publication date: 17-Oct-2022
    • (2020)Enhancing information retrieval performance by using social analysisSocial Network Analysis and Mining10.1007/s13278-020-00635-w10:1Online publication date: 8-Apr-2020
    • (2019)Second-Order CoSimRank for Similarity Measures in Social NetworksICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761899(1-6)Online publication date: May-2019
    • (2019)Personalized Social Query Expansion Using Social AnnotationsTransactions on Large-Scale Data- and Knowledge-Centered Systems XL10.1007/978-3-662-58664-8_1(1-25)Online publication date: 5-Jan-2019
    • (2019)Exploiting Social Data to Enhance Web SearchFuture Data and Security Engineering10.1007/978-3-030-35653-8_38(593-607)Online publication date: 20-Nov-2019
    • (2018)Lightweight Tag-Aware Personalized Recommendation on the Social Web Using Ontological SimilarityIEEE Access10.1109/ACCESS.2018.28507626(35590-35610)Online publication date: 2018
    • (2018)Accessing Information with Tags: Search and RankingSocial Information Access10.1007/978-3-319-90092-6_9(310-343)Online publication date: 3-May-2018
    • (2017)Personalized query expansion utilizing multi-relational social data2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)10.1109/SMAP.2017.8022669(65-70)Online publication date: Jul-2017
    • Show More Cited By

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