1. A Personalized Search Engine Based on Web Snippet Hierarchical Clustering Paolo Ferragina, Antonio Gulli Dipartimento di Informatica, Pisa ferragina@di.unipi.it WWW 2005 H.3 [Information Storage And Retrieval] Content Analysis and Indexing, Information Search and Retrieval,Online Information Services; Keywords : Web Snippets Clustering, Search Engines, Information Extraction,New Search Applications and Interfaces, Personalized Web Ranking

2. 2 ABSTRACT 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. Personalized search engines have been introduced with the aim of improving search results by focusing on the users, rather than on their submitted queries. Users can navigate through the hierarchy driven by their search needs. This is especially useful for informative, polysemous and poor queries.

3. 3 INTRODUCTION Web-snippet clustering is an innovative approach to help users in searching the web. Various industrial systems implement web-snippet clustering in their (meta-)search engines: Vivisimo, Mooter, Copernic, iBoogie, Kartoo, Groxis, Dogpile and Clusty. Vivisimo from 2001 to 2003 : “best meta-search engine award” assigned by SearchEngineWatch.com It consists of clustering the snippets returned by a (meta- )search engine into a hierarchy of folders. snakeT: http://snaket.di.unipi.ithttp://snaket.di.unipi.it 16 search engines about Web, Blog, News, Books... The interface similar to Vivisimo

4. 4 INTRODUCTION

5. 5 RELATED WORK The first web - clustering softwares (sigir-96)

6. 6 The anatomy of snakeT