Mark Last

Senior Academic

Design and implementation of a web mining system for organizing search engine results

Adam Schenker, Mark Last, Abraham Kandel

We present the design and implementation of a web mining system that creates a hierarchical clustering of web documents retrieved by commercial web search engines. The cluster hierarchy is produced by a novel method called the Cluster Hierarchy Construction Algorithm (CHCA) and it can be used to explore the topics of interest related to the search query and their relationships. We discuss important design issues for our system, including stemming and dimensionality reduction, as well as some implementation details. We show examples of system results, compare them with results from similar systems, and analyze the responses to a survey of the system's users.

Publication language English
Pages 607-625
Journal International Journal of Intelligent Systems
Volume 20
Issue number 6
Publication status Published - 01.06.2005

ASJC Scopus subject areas

Software
Theoretical Computer Science
Human-Computer Interaction
Artificial Intelligence
Access to Document
10.1002/int.20086
Other files and links
Link to publication in Scopus