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FuzzFind : Calibrating Social and Algorithmic Search

If the title of the post appeared too technical, then my apologies. I wanted to convey in a nutshell that FuzzFind, the meta-social-search mashup combines results from search engines and social bookmarking sites on an equal footing (an achievement for social bookmarking I must say). The approach should fetch relevant results since social bookmarking is humans at work and search engines is about algorithms.

The site allows users to calibrate the extent to which they prefer their results from the different search engines.

In the words of the FuzzFind team itself :

The calibration meters (sliders) act purely as a quantitative measure. It gives you the capability to set the importance of the various search sources based on your personalized needs, which helps to improve the relevance of the search result rankings. Also, it remembers your previous settings for subsequent searches.

The size of the search engines image beside the result link provides a clue on how relevant the result was to the particular engine. And I personally love the little squiggle the search box makes when you mouse-move over the red fuzzy icon.

Also, there is no mixing of paid or sponsored links within the search results.

Using meta search engines is emerging as a staple to web searchers. It is a necessity to obtain a holistic information on any topic. Though it is true that Google does a great work with search, there are differences in the approach taken by the different engines (or at least a variation in degree of various techniques). Hence meta search engines should provide a holistic experience and over time I am sure that users would come across nuggets of information that they would have missed out on had they remained stuck to just one or two of the engines.

Also, more projects like these make it easier for users to compare the results from various engines (and perhaps in the long run tune open source engines such as Wikia).

FuzzFind will be incorporating more search and bookmarking engines in future. Here’s wishing them the best in this venture.

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FuzzFind : Calibrating Social and Algorithmic Search

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