Microsoft Technology Licensing, LLC

Kieran Richard McDonald

Sanaz Ahari

Ran Gilad-Bachrach

Nitin Agrawal

Nipoon Malhotra

Kumaresh Pattabiraman

Christopher A Meyers

Tapas Kanungo

Kuansan Wang

Richard Junqiang Qian

Srinath Reddy Aaleti

Ashok Ponnuswami

Alec John Berntson

Luke Evans Simon

Muhammad Arif Iqbal

Computer-readable media, computer systems, and computing devices for facilitating presentation of search result items having varying prominence is provided. The method includes referencing a search result item to be presented within a search results page in response to a search query. Thereafter, a determination is made that a size prominence of the search result item is to be modified. Such a determination can be based on a result attribute(s) associated with the search result item and a result attribute(s) associated with other search result items within the search results page. The size of the search result item is adjusted in accordance with the determination that the size prominence of the search result item is to be modified.

Presenting search result items having varied prominence

Technologies are described herein for placing search results on a search engine results page (SERP). A query may be received. The query may be transmitted to a plurality of search result providers. A first set of search results and a second set of search results may be received from the search result providers. Intent features may be extracted from the first set of search results. User intent of the second set of search results may be inferred based on the extracted intent features. The first set of search results and the second set of search results may be ranked based on the inferred user intent. The SERP may be rendered according to the ranked first set and second set of search results.

Placement of search results using user intent

A computer-implemented method, a computer system, and computer media for discovering links in scripts are provided. The computer system includes a crawler, a rules engine, and an index that are utilized to store links generated by scripts located in webpages in the index. The crawler traverses a network to locate webpages having scripts. The rules engine parses the located webpages and extracts the scripts based on rules that are satisfied by segments of the extracted scripts. The rules engine evaluates the segments of the extracted scripts to generate links. After the rules engine validates the links, the rules engine transmits the links to the index for storage.

Link discovery from web scripts

This patent application pertains to answer model comparison. One implementation can determine a first frequency at which an individual answer category appears in an individual slot on a query results page when utilizing a first model. The method can ascertain a second frequency at which the individual answer category appears in the individual slot on the query results page when utilizing a second model. The method can calibrate the second model so that the second frequency approaches the first frequency.

Answer model comparison

Methods and computer-storage media having computer-executable instructions embodied thereon that facilitate generating a machine-learned model for ranking search results using click-based data are provided. Data is referenced from user queries, which may include search results generated by general search engines and vertical search engines. A training set is generated from the search results and click-based judgments are associated with the search results in the training set. Based on click-based judgments, identifiable features are determined from the search results in a training set. Based on determining identifiable features in a training set, a rule set is generated for ranking subsequent search results.

Ranking search results using click-based data

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Kieran Richard McDonald