WebQuery: Searching and Visualizing the Web Through Connectivity

Abstract Finding information located somewhere on the World-Wide Web is an error-prone and frustrating task. The WebQuery system offers a powerful new method for searching the Web based on connectivity and content. We do this by examining links among the nodes returned in a keyword-based query. We then rank the nodes, giving the highest rank to the most highly connected nodes. By doing so, we are finding “hot spots” on the Web that contain information germane to a user's query. WebQuery not only ranks and filters the results of a Web query, it also extends the result set beyond what the search engine retrieves, by finding “interesting” sites that are highly connected to those sites returned by the original query. Even with WebQuery filtering and ranking query results, the result sets can be enormous. So, we need to visualize the returned information. We explore several techniques for visualizing this information—including cone trees, 2D graphs, 3D graphs, lists, and bullseyes-and discuss the criteria for using each of the techniques.