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Can social bookmarking enhance search in the web?

Published: 18 June 2007 Publication History

Abstract

Social bookmarking is an emerging type of a Web service that helps users share, classify, and discover interesting resources. In this paper, we explore the concept of an enhanced search, in which data from social bookmarking systems is exploited for enhancing search in the Web. We propose combining the widely used link-based ranking metric with the one derived using social bookmarking data. First, this increases the precision of a standard link-based search by incorporating popularity estimates from aggregated data of bookmarking users. Second, it provides an opportunity for extending the search capabilities of existing search engines. Individual contributions of bookmarking users as well as the general statistics of their activities are used here for a new kind of a complex search where contextual, temporal or sentiment-related information is used. We investigate the usefulness of social bookmarking systems for the purpose of enhancing Web search through a series of experiments done on datasets obtained from social bookmarking systems. Next, we show the prototype system that implements the proposed approach and we present some preliminary results.

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Cited By

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  • (2021)Content and link-structure perspective of ranking webpagesComputer Science Review10.1016/j.cosrev.2021.10039740:COnline publication date: 1-May-2021
  • (2020)Bewertung der Informationsqualität im Enterprise 2.0Daten- und Informationsqualität10.1007/978-3-658-30991-6_12(211-221)Online publication date: 20-Nov-2020
  • (2019)Towards Better Support for Exploratory Search through an Investigation of Notes-to-self and Notes-to-shareProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331309(1093-1096)Online publication date: 18-Jul-2019
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cover image ACM Conferences
JCDL '07: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
June 2007
534 pages
ISBN:9781595936448
DOI:10.1145/1255175
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 June 2007

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Author Tags

  1. metadata
  2. pagerank
  3. social bookmarking
  4. social search

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JCDL07
JCDL07: Joint Conference on Digital Libraries
June 18 - 23, 2007
BC, Vancouver, Canada

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Overall Acceptance Rate 415 of 1,482 submissions, 28%

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Cited By

View all
  • (2021)Content and link-structure perspective of ranking webpagesComputer Science Review10.1016/j.cosrev.2021.10039740:COnline publication date: 1-May-2021
  • (2020)Bewertung der Informationsqualität im Enterprise 2.0Daten- und Informationsqualität10.1007/978-3-658-30991-6_12(211-221)Online publication date: 20-Nov-2020
  • (2019)Towards Better Support for Exploratory Search through an Investigation of Notes-to-self and Notes-to-shareProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331309(1093-1096)Online publication date: 18-Jul-2019
  • (2018)Bewertung der Informationsqualität im Enterprise 2.0Daten- und Informationsqualität10.1007/978-3-658-21994-9_12(209-219)Online publication date: 12-Jun-2018
  • (2018)Social SearchSocial Information Access10.1007/978-3-319-90092-6_7(213-276)Online publication date: 3-May-2018
  • (2018)Social Web SearchEncyclopedia of Social Network Analysis and Mining10.1007/978-1-4939-7131-2_261(2787-2793)Online publication date: 12-Jun-2018
  • (2017)Revision of the learning resources modeling concept by Recursive Entity Modeling Method (REMM)Proceedings of the 2nd international Conference on Big Data, Cloud and Applications10.1145/3090354.3090446(1-6)Online publication date: 29-Mar-2017
  • (2017)Asynchronous social search as a single point of access to informationLibrary Hi Tech10.1108/LHT-01-2017-000735:4(649-664)Online publication date: 20-Nov-2017
  • (2017)The Role of Context for User Annotations in Searching Shared MaterialsAdvances in Web-Based Learning – ICWL 201710.1007/978-3-319-66733-1_10(91-100)Online publication date: 19-Aug-2017
  • (2017)Social Media Usage in Higher Education in Online Business ProgramsOn the Line10.1007/978-3-319-62776-2_16(203-218)Online publication date: 14-Sep-2017
  • Show More Cited By

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