A survey of Web clustering engines
Author(s) -
Claudio Carpineto,
Stanisław Osiński,
Giovanni Romano,
Dawid Weiss
Publication year - 2009
Publication title -
acm computing surveys
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.079
H-Index - 163
eISSN - 1557-7341
pISSN - 0360-0300
DOI - 10.1145/1541880.1541884
Subject(s) - cluster analysis , computer science , information retrieval , data mining , search engine , preprocessor , brown clustering , conceptual clustering , fuzzy clustering , cure data clustering algorithm , machine learning , artificial intelligence
Web clustering engines organize search results by topic, thus offering a complementary view to the flat-ranked list returned by conventional search engines. In this survey, we discuss the issues that must be addressed in the development of a Web clustering engine, including acquisition and preprocessing of search results, their clustering and visualization. Search results clustering, the core of the system, has specific requirements that cannot be addressed by classical clustering algorithms. We emphasize the role played by the quality of the cluster labels as opposed to optimizing only the clustering structure. We highlight the main characteristics of a number of existing Web clustering engines and also discuss how to evaluate their retrieval performance. Some directions for future research are finally presented.
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