In recent years there have been novel

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Approaches to the topic of searching data on the Internet. One notable example is Blekko , created with the idea of ​​adding editorial meaning to search information. Blekko uses parameters called “slashtags” to differentiate or organize the results in a search. Instead of using the links to a site to rate its relevance, its algorithm uses the content of the site and the context of the search content on the site, and it is possible for its users to rate the results to improve them using the collective intelligence of its community. A positive effect of this approach is the reduction of SPAM sites and makes search engine optimization (SEO) techniques to promote sites with irrelevant content.

Another approach to search is that taken by Stephen Wolfram in creating the Wolfram Alpha answer machine , which instead of returning lists of sites, uses algorithms that analyze search queries in natural language to give them Albania Mobile Database context and, based on the question, generates a single response page with information obtained from multiple sites and pages on the Web. Wolfram Alpha not only analyzes, stores and categorizes results, but applies intelligence to them and processes the information to generate results from information on the Web. For example, the question “What is the 52nd country with the lowest GDP per person?” returns the answer “Nicaragua, with $1,160 dollars per year.” Wolfram Alpha changes the search model from keywords to a natural language one and is in fact used by Siri on the iPhone to answer factual questions.