.about
contextDigger 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.The tool also helps you in formulating new search queries. Selected keywords are automatically placed in the search field and a simple click on "search" will restart the process with the new parameters. This way, you can progressively dig deeper into the complexity of the Web. Clicking on the "inbound" button, which is displayed for every individual result, will show sites that point to the site in question (via Yahoo Site Explorer); the "related" button will bring up sites with similar content (via Google’s REST API).
contextDigger makes use of the beautiful jQuery JavaScript library and was written by Bernhard Rieder and Alexandre Beaugrand.
.concept
Web 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.A second thing we are trying to show with our application is that API based development can effectively enhance the search experience and help in showing that alternative pathways for search are feasible. We hope that this will contribute to the establishment of legal frameworks that give API developers certain rights: for the moment, whenever an API provider decides to modify (or discontinue) a service, developers have no means of recourse other than complaining loudly. This means that experiments with APIs entail significant risk, which may discourage projects that take considerable time and money to build and maintain if they end up being short-lived. By showing how technological experiments can open up our ideas about how things are done, and how they might be done differently, we aim to underline that there may be good reasons to think about a licensing model (perhaps similar to creative commons) that gives certain guarantees to API developers. In the area of search, no developer can pretend to be able to rival the huge indexes of big search companies. Experiments with these technologies depend on stable access to these indexes.
.preferences
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