Searching the web by constrained spreading activation

Intelligent Information Retrieval is concerned with the application of inte lligent techniques, like for example semantic networks, neural networks and inference nets to Information Retrieval. This field of research has seen a number of applications of Constrained Spreading Activation (CSA) technique s on domain knowledge networks. However, there has never been any applicati on of these techniques to the World Wide Web. The Web is a very important i nformation resource, but users find that looking for a relevant piece of in formation in the Web can be like 'looking for a needle in a haystack'. We w ere therefore motivated to design and develop a prototype system, WebSCSA ( Web Search by CSA), that applied a CSA technique to retrieve information fr om the Web using an ostensive approach to querying similar to query-by-exam ple. In this paper we describe the system and its underlying model. Further more, we report on an experiment carried out with human subjects to evaluat e the effectiveness of WebSCSA. We tested whether WebSCSA improves retrieva l of relevant information on top of Web search engines results and how well WebSCSA serves as an agent browser for the user. The results of the experi ments are promising, and show that there is much potential for further rese arch on the use of CSA techniques to search the Web. (C) 2000 Elsevier Scie nce Ltd. All rights reserved.