.aboutcontextDigger is a search mashup that generates a "termcloud" and a "cluster" view to present and navigate search results and formulate new queries. contextDigger takes your query and tries to automatically extend search parameters via terms received from the Bing API’s "related search" feature and an analysis of popular delicious posts. These terms are then used to load 1000 links from Yahoo’s BOSS service. BOSS delivers a list of extracted keywords (~20) for every result and these are the basis for contextDigger’s services. The termcloud-view allows users to explore search results by simply clicking on a term; results associated with that term will be displayed in a list. You can also switch to the cluster-view which analyzes relations between keywords (co-occurrence) and groups them into a customizable number of thematic clusters. Both views are based on the concept of faceted navigation: if two or more keywords are activated, only sites related to all of these terms will be displayed. This way, you can browse the 1000 results by progressively selecting and deselecting keywords.
.conceptWeb Search engines most often operate on the idea that their tools are supposed to represent the fastest way between a user’s search query and a site that will represent a fitting information content to satisfy a "information need". The main challenge is therefore about building ranking algorithms that will find the "best" site and put it into first place. While this approach has been highly successful it also neglects the user’s ability to interact, select, navigate, analyze – in short, to be an active agent and a stakeholder in the search process. Our proposal is the technical manifestation of a simple concept: instead of reducing the search phase to a minimum we believe that there is much to be gained by presenting a semantically rich interface to users; this interface can be used to either navigate in a list of results (1000 in the case of our current prototype) or to refine the search query. The “termcloud” and “cluster” views give a quick overview of a topic by showing which terms are significant, their relative frequency and the relations that exist between them. This way the user gets an idea of the topic before even visiting a Web site from the result list. We hope that this approach will help users in digging deeper than the first couple of results and explore the regions of the Web that might not be so easy to find with a regular, hit-driven search engine.
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