Glinden points to a post from Ken Moss (GM, MSN Search) wherein he says,In collaboration with Chris Burges and others from Microsoft ResearchMSN now hase a brand new ranker. The new ranker has improved ther relevance and perhaps most importantly gives MSN a platform to move forward on quicker than before. This new ranker also is based on technology with an awesome name - it's a "Neural Net." A number of new operators that will enable narrowing down search to exactly what one is looking for.is also added. We’ve added FileType:, one of the most asked for operators, which restricts documents to a particular filetype. InAnchor:, InURL:, InTitle:, and InBody: are now available to find keywords in a particular part of the document, or in anchor text pointing to a document. We’ve augmented the Link: keyword that finds documents that link to a particular page with LinkDomain:, which finds documents that point to any page in a domain. Finally, we’ve added a new experimental operator called Contains:. Contains: returns documents that contain hyperlinks to documents with a particular file extension; for example, contains:wma returns documents that contain a link to a WMA file. Grer points out, Chris Burges was the lead author on a 2005 paper called "Learning to Rank using Gradient Descent" that does appear to try to use neural networks for relevance rank.Applying machine learning techniques to relevance rank for web search is common, using neural networks is not. The contribution and success of applying Neural network techniques for search needs to be closely watched.
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