Microsoft Technology Licensing, LLC

Andrew Samuel Laucius

Darren Arthur Shakib

Jonathan A Forbes

Christopher J Burges

Rangan Majumder

Keith Andrew Birney

Leon C W Wong

Irina Matveeva

Eytan D Seidman

Timo Burkard

Javier Tordable

Ramkumar Rajendran

Systems, computer-implemented methods, and computer-readable media for modifying the rank of search result items returned by a search engine are provided. A search engine determines a plurality of search result items that satisfy a user query and the order the search result items are to be presented to a user. A rank modifier determines whether any modification should be made to the rank of each search result item identified by the search engine. The rank of search result items identified as potential spam may be demoted while the rank of search result items identified to be in the language of the search query, having a high click-through rate, or as containing adjacent search terms from the search query may be promoted. The search result items are presented according to modified ranking to the querying user.

Modifying relevance ranking of search result items

A unique system and method that facilitates improving the ranking of items is provided. The system and method involve re-ranking decreasing subsets of high ranked items in separate stages. In particular, a basic ranking component can rank a set of items. A subset of the top or high ranking items can be taken and used as a new training set to train a component for improving the ranking among these high ranked documents. This process can be repeated on an arbitrary number of successive high ranked subsets. Thus, high ranked items can be reordered in separate stages by focusing on the higher ranked items to facilitate placing the most relevant items at the top of a search results list.

Ranking results using multiple nested ranking

A system and method facilitating incremental web crawl(s) using chunk(s) is provided. The system can be employed, for example, to facilitate a web-crawling system that crawls (e.g., continuously) the Internet for information (e.g., data) and indexes the information so that it can be used as part of a web search engine. The system facilitates incremental re-crawls and/or selective updating of information (e.g., documents) using a structure called a chunk to simplify the process of an incremental crawl. A chunk is a set of documents that can be manipulated as a set (e.g., of up to 65,536 (64K) documents). 'Document' refers to a corpus of data that is stored at a particular URL (e.g., HTML, PDF, PS, PPT, XLS, and/or DOC Files etc.) A chunk is created by an indexer. The indexer can place into a chunk documents that have similar property(ies). These property(ies) include but are not limited to: average time between change and average importance. These property(ies) can be stored at the chunk level in a chunk map. The chunk map can then be employed (e.g., on a daily basis) to determine which chunk(s) should be re-crawled.

Incremental web crawler using chunks

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Seattle, WA, United States of America

Andrew Samuel Laucius