A New Query Suggestion Algorithm for Taxonomy-based Search Engines

Abstract

The objective of this work is the realization of an algorithm to provide a query suggestion feature in order to support the search engine of a commercial web site. Starting from web server logs, our solution creates a model analyzing the queries submitted by the users. Given a submitted query, the system searches the most adequate queries to suggest. Our method implements an already known session based proposal enriching it by exploiting specific information available in the current context: the category the user is browsing on the web site and a solution to overcome the limits of a pure session based approach considering also similarity between queries. Quantitative and qualitative experiments show that the proposed model is suitable in terms of resources employed and user's satisfaction degree.