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Nutch-based ObjectSearch.com Launches

WebProNews
Staff Writer
Published: 2004-04-27

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Aiming to provide users with best search results, free website submission and unbiased website ranking, ObjectSearch.com has launched an open source search engine based on Nutch.org's search. ObjectSearch looks to solve problems related to search result manipulation and information overload.

ObjectSearch claims that their open source approach provides an "alternative to commercial web search engines. Only open source search results can be fully trusted to be without bias." This premise goes against the major search engines in the methods in which they rank search results.

The following is a description taken from ObjectSearch's about page and does a good job of explaining the engine's approach to search results.
"All existing major search engines have proprietary ranking formulas, and will not explain why a given page ranks as it does. Additionally, some search engines determine which sites to index based on payments, rather than on the merits of the sites themselves.

Objects Search, on the other hand, has nothing to hide and no motive to bias its results or its crawler in any way other than to try to give each user the best results possible."

Each result that appears on OS's results page contains three different links. They have cached links, which displays the page that OS downloaded. Results have an explanation link that describes how the site received its ranking, and finally the result links feature an anchor link that shows a list of incoming anchors that have been indexed for the page in question.

ObjectSearch uses a cluster method in its results. In fact, OS claims to be the first search engine "which cluster[s] its own search results unlike other meta search engines, which get their search results from other search engines." To accomplish this, OS uses what's known as a "Clustering Engine".

A description of OS's approach to search results and clustering appears on their about page: "one approach is to automatically group search results into thematic categories, called clusters. Assuming clusters descriptions are informative about the documents they contain, the user spends much less time following irrelevant links."

The group feels this approach will cut down on information overload and make search results more relevant.

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