Adapting to the user's internet search strategy on small devices

World Wide Web search engines typically return thousands of results to the users. To avoid users browsing through the whole list of results, search engines use ranking algorithms to order the list according to predefined criteria. In this paper, we present Toogle, a front-end to the Google search engine for mobile phones offering web browsing. For a given search query, Toogle first ranks results using Google’s algorithm and, as the user browses through the result list, uses machine learning techniques to infer a model of her search goal and to adapt accordingly the order in which yet-unseen results are presented. We report preliminary experimental results that show the effectiveness of this approach. Categories and Subject Descriptors I.3.6 [Computer Graphics]: Methodology and Techniques – Interaction techniques, H.3.4 [Information Storage and Retrieval]: Systems and Software – User profiles and alert services. General Terms Algorithms, Experimentation, Human Factors. Keywords I...

• Type: Conference
• Year: 2003
• Where: IUI
• Authors: Jean-David Ruvini
• Keywords: Google Search Engine, IUI 2003, Search Engine, Software Engineering, Web Search Engines