2005 APersonalizedSearchEngBasedOnWebSnipHierClust

• (Ferragina & Gulli, 2005) ⇒ Paolo Ferragina, Antonio Gulli. (2005). “A Personalized Search Engine Based on Web-Snippet Hierarchical Clustering.” In: Proceedings of International World Wide Web Conference (WWW 2005).

Subject Headings: Hierarchical Clustering Algorithm, Text Document Clustering Algorithm, SnakeT Search Service, Clusty Search Service.

Cited By

~153 http://scholar.google.com/scholar?cites=11052246651071444809

Quotes

Abstract

• In this paper we propose a hierarchical clustering engine, called snaket, that is able to organize on-the-fly the search results drawn from 16 commodity search engines into a hierarchy of labeled folders. The hierarchy offers a complementary view to the flat-ranked list of results returned by current search engines. Users can navigate through the hierarchy driven by their search needs. This is especially useful for informative, polysemous and poor queries. SnakeT is the first complete and open-source system in the literature that offers both hierarchical clustering and folder labeling with variable-length sentences. We extensively test SnakeT against all available web-snippet clustering engines, and show that it achieves efficiency and efficacy performance close to the best known engine Vivisimo.com. Recently, personalized search engines have been introduced with the aim of improving search results by focusing on the users, rather than on their submitted queries. We show how to plug SnakeT on top of any (un-personalized) search engine in order to obtain a form of personalization that is fully adaptive, privacy preserving, scalable, and non intrusive for underlying search engines.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2005 APersonalizedSearchEngBasedOnWebSnipHierClust	Paolo Ferragina Antonio Gulli			A Personalized Search Engine Based on Web-Snippet Hierarchical Clustering			http://dx.doi.org/10.1145/1062745.1062760	10.1145/1062745.1062760