Personalised Search profiles Kaltix, a stealth search start-up out of Stanford University:

Kaltix hopes to improve upon PageRank, with an attempt to speed up the underlying PageRank computations. That, in turn, could lay the groundwork for a breakthrough in a cutting-edge area of Web search development known as “personalization,” which aims to sort search results based on the specific needs and interests of individuals, instead of the consensus approach pioneered by Google.

The personalization of search tools entails matching results to user profiles. These profiles could include data such as zip code, birth date or individual search history. For example, the keyword “jaguar” might place car sites at the top of search results for someone who had recently visited automobile Web sites, but might lead off with Web sites about the cat for someone whose surfing history showed an interest in animals.

Personalization techniques include collecting data from the search user directly, as well as putting algorithms to work behind the scenes. With a little information voluntarily submitted by a searcher, an engine could localize search for results in German or French or segment listings to show only 15 out of the top 100 links. An advanced algorithmic technique might apply keyword-pattern analysis in order to examine an individual’s search history and guess what the object might be of the next search request.

The main task will be getting the user interface right. That means giving people notice of what data has been collected, where that data will be stored and how it will be used. It also means giving users the choice of changing data or removing it.


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Rajesh Jain

An Entrepreneur based in Mumbai, India.