What good is a search engine if the results it provides aren't relevant to the query being performed? The answer? Not much. The largest search index in the world doesn't amount to much if you don't have an algorithm that can successfully provide results related to the question being posed.
WebProWorld Because relevance is such an important characteristic, many who study the industry surveys to discover what people consider relevant when it comes to search results. Evidently, the commitment to relevance is also of great importance to the developers at MSN Search, who recently began using a new method to determine relevance within their search results called the Neural Net. According to Barry at SERoundtable, the Neural Net technology is based on RankNet, a method of relevance ranking being researched by the MSN team. Gary Linden came across MSN's I'd love to give you a one sentence summary of what it does, but so far, that escapes me despite reading the paper several times." Danny also feels the RankNet system "recognizes" what is a good result and what is not and ranks them accordingly. He also admits that this line of thinking may come from him misunderstanding their pdf. While the white paper is quite dense, their use of the Neural Net has already paid dividends, at least in Japanese field tests and other examples provided on the Murdok. Visit Murdok for theSuggest a Correction
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