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Social Book Search Reranking with Generalized Content-Based Filtering

Published: 03 November 2014 Publication History

Abstract

Semantically searching and navigating products (e.g., on Taobao.com or Amazon.com) with professional metadata and user-generated content from social media is a hot topic in information retrieval and recommendation systems, while most existing methods are specifically designed as a purely searching system. In this paper, taking Social Book Search as an example, we propose a general search-recommendation hybrid system for this topic. Firstly, we propose a Generalized Content-Based Filtering (GCF) model. In this model, a preference value, which flexibly ranges from 0 to 1, is defined to describe a user's preference for each item to be recommended, unlike conventionally using a set of preferable items. We also design a weighting formulation for the measure of recommendation. Next, assuming that the query in a searching system acts as a user in a recommendation system, a general reranking model is constructed with GCF to rerank the initial resulting list by utilizing a variety of rich social information. Afterwards, we propose a general search-recommendation hybrid framework for Social Book Search, where learning-to-rank is used to adaptively combine all reranking results. Finally, our proposed system is extensively evaluated on the INEX 2012 and 2013 Social Book Search datasets, and has the best performance (NDCG@10) on both datasets compared to other state-of-the-art systems. Moreover, our system recently won the INEX 2014 Social Book Search Evaluation.

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Cited By

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  • (2023)On the current state of query formulation for book searchArtificial Intelligence Review10.1007/s10462-023-10483-756:10(12085-12130)Online publication date: 19-Apr-2023
  • (2021)Improving social book search using structure semantics, bibliographic descriptions and social metadataMultimedia Tools and Applications10.1007/s11042-020-09811-880:4(5131-5172)Online publication date: 1-Feb-2021
  • (2020)Social book search: the impact of the social web on book retrieval and recommendationMultimedia Tools and Applications10.1007/s11042-019-08591-079:11-12(8011-8060)Online publication date: 3-Jan-2020
  • Show More Cited By

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      cover image ACM Conferences
      CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
      November 2014
      2152 pages
      ISBN:9781450325981
      DOI:10.1145/2661829
      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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      Publication History

      Published: 03 November 2014

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      Author Tags

      1. generalized content-based filtering
      2. learning to rank
      3. search-recommendation hybrid system
      4. social book search

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      CIKM '14 Paper Acceptance Rate 175 of 838 submissions, 21%;
      Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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      Cited By

      View all
      • (2023)On the current state of query formulation for book searchArtificial Intelligence Review10.1007/s10462-023-10483-756:10(12085-12130)Online publication date: 19-Apr-2023
      • (2021)Improving social book search using structure semantics, bibliographic descriptions and social metadataMultimedia Tools and Applications10.1007/s11042-020-09811-880:4(5131-5172)Online publication date: 1-Feb-2021
      • (2020)Social book search: the impact of the social web on book retrieval and recommendationMultimedia Tools and Applications10.1007/s11042-019-08591-079:11-12(8011-8060)Online publication date: 3-Jan-2020
      • (2020)Social Book Search: a surveyArtificial Intelligence Review10.1007/s10462-018-9647-x53:1(95-139)Online publication date: 1-Jan-2020
      • (2019)Book search using social information, user profiles and query expansion with Pseudo Relevance FeedbackApplied Intelligence10.1007/s10489-018-1383-z49:6(2178-2200)Online publication date: 1-Jun-2019
      • (2018)Book Search using social information2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)10.1109/ICACCCN.2018.8748865(510-513)Online publication date: Oct-2018
      • (2016)ISART: A Generic Framework for Searching Books with Social InformationPLOS ONE10.1371/journal.pone.014847911:2(e0148479)Online publication date: 10-Feb-2016
      • (2014)Social Book Search with Pseudo-Relevance FeedbackNeural Information Processing10.1007/978-3-319-12640-1_25(203-211)Online publication date: 2014

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