A personalized search engine based on web-snippet hierarchical clustering

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 S...

• Type: Conference
• Year: 2005
• Where: WWW
• Authors: Paolo Ferragina, Antonio Gulli
• Keywords: Current Search Engines, Internet Technology, Search Engines, Web-snippet Clustering Engines, WWW 2005