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Using social annotations for search results clustering

Aliakbary, S ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-540-89985-3_147
  3. Publisher: 2008
  4. Abstract:
  5. Clustering search results helps the user to overview returned results and to focus on the desired clusters. Most of search result clustering methods use title, URL and snippets returned by a search engine as the source of information for creating the clusters. In this paper we propose a new method for search results clustering (SRC) which uses social annotations as the main source of information about web pages. Social annotations are high-level descriptions for web pages and as the experiments show, clustering based on social annotations yields good clusters with informative labels. © 2008 Springer-Verlag
  6. Keywords:
  7. Clustering ; Clustering methods ; Clustering-based ; High level description ; Search results ; Search results clustering ; Social Annotation ; Tagging ; Web page ; Computer science ; Information retrieval ; Search engines ; World Wide Web ; Data mining
  8. Source: 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, 9 March 2008 through 11 March 2008 ; Volume 6 CCIS , 2008 , Pages 976-980 ; 18650929 (ISSN); 3540899847 (ISBN); 9783540899846 (ISBN)
  9. URL: https://link.springer.com/chapter/10.1007/978-3-540-89985-3_147