Microsoft Technology Licensing, LLC

Manish Mittal

Marcelo Medeiros De Barros

Aman Singhal

Siddharth S Shenoy

Prateek Tiwari

Marcelo De Barros

Vinod Krishnan Koduvayoor Subramanian

Ayan Banerjee

Samir Bathla

Nabeel Kaushal

Dilip Krishna Pai

Mikhail Parakhin

Michael Andrews

Girish Bablani

Hui Shi

Satya Pradeep Kanduri

Joseph Forsmann

Mark Killow

Monte C Christensen

Theodor Ilie

Adam Edlavitch

Feng Qi

Systems and methods are provided for determining contextual objects related to web content. Web content may include one or more elements, which may be extracted from the web content and analyzed to identify any contextual objects. The web content elements may be hyperlink elements, and contextual objects may be identified based on the hyperlink elements. A dominant entity may be identified for the web content, and contextual objects relating to the dominant entity may be identified. When a request for web content is received, contextual objects may be provided with the requested content. Personalized contextual objects may be selected from the identified contextual objects based on data associated with the request for web content. Selection of a contextual object may result in navigation to a browsing environment associated with the selected contextual object.

Identifying contextual objects from web content

Unique application identification (UAID) stamping for automated classification of an implicit query as an application intent query from web results for enabling improved delivery of applications as a search result is provided. An application indexing engine identifies web resources related to an app, and tags the resources with a unique application identifier associated with the app. Accordingly, an implicit query where a web resource responsive to the query is related to the app triggers classification of the query as an app-intent query, enabling the app to be provided as an app result in response to the query. The app is presented to a user, who may selectively download the app.

Automated application linking

A plurality of category application queries can be processed, including identifying an associated list of results for each of the category application queries, with each list of results listing one or more applications. A cluster of the category application queries that each have a category in common in an application category stamp can be identified. A proximity graph for the category application queries in the cluster can be generated. The proximity graph can indicate similarity scores based at least in part on numbers of applications in common for lists of results associated with the category application queries in pairs of queries in the cluster. Lists each having one or more suggested alternative category application queries for category application queries in the cluster can be generated, with the generating of the lists of one or more suggested alternative category application queries being based at least in part on the similarity scores.

Computer application query suggestions

A limited first set of search engine results can be retrieved from running an application query, with the limited first set of results being limited to applications associated with a first set of application platform(s). Categories of applications referenced in the limited first set of results can be identified, and a category stamp can be generated for the query based on applications in the first set of results that are associated with each of multiple categories. A limited second set of search engine results can be retrieved from running the query. The limited second set of results can be limited to applications associated with a second set of application platform(s), with the second set of results being limited to applications in a category corresponding to the category stamp for the query. An application list for the query can be generated using the limited second set of results.

Cross-platform computer application query categories

Systems and methods are provided for monitoring the performance of a network with respect to providing results for user requests. A user request can correspond to a search query, an entry of a uniform resource locator (URL) or other address for a document on a network, or another type of request. A plurality of user requests are aggregated, such as based on logs of search query or browsing activity. A representative group of user requests is selected and then submitted in order to evaluate the results provided. Based on a heuristic analysis of the results, an alert can be provided to indicate potential performance problems in the network environment.

Heuristic analysis of responses to user requests

Web applications, systems and services, which are prone to cyber-attacks, can utilize an adaptive fuzzing system and methodology to intelligently employ fuzzer technology to test web site pages for vulnerabilities. A breadth first search and minimal fuzzing testing is performed on identified pages of a web site looking for either a vulnerability or the potential for a vulnerability. Heuristics are gathered and/or generated on each tested web page to determine a vulnerability score for the page that is an indication of the page's potential for hosting a vulnerability. When a page is discovered with a vulnerability score that indicates the page has the potential for a vulnerability a depth first search and expanded fuzzing testing is performed on one or more branches of the web site that begin with the page with the potential vulnerability.

Adaptive fuzzing system for web services

Query suggestions are generated based on a Breadth-First-Search having a configurable decaying radius. A computer system receives an initial set of semantically similar queries. The computer system expands the set to include related terms. The set of related terms is included in the initial set. The expansion process is repeated for each query or related term in the set. The radius may be reduced for each subsequent related term added to the query. The process may stop when the radius reaches a specified threshold, e.g., a predetermined number of queries or terms for the set is reached. The set includes the related terms and search queries. The set may be used for, among other things, suggesting related terms to a researcher, improving search engine performance, or selecting appropriate advertisements.

Automatic generation of semantically similar queries

Outlier images&#x2014;those images that differ substantially from other images in a set&#x2014;can be automatically identified. One or more penalty values can be assigned to each image that quantifies how different that image is from others in the set. A threshold can be determined based on the set of penalty values. Each image whose penalty values are above the threshold is an outlier image. The penalty values can be the sum of per-pixel penalty values multiplied by the number of pixels with nonzero penalty values. A per-pixel penalty value can be the difference between a color value for that pixel and a predetermined range of color values, based on corresponding pixels in other images. The per-pixel penalty value can be determined for each component color and then optionally summed together. The threshold penalty values can be adjusted to provide for greater, or less, sensitivity to differences among the images.

Automated identification of image outliers

An image may be accepted from a vendor, and the image may be submitted to an image analysis system. The image analysis system may determine whether the image is a not found image or a true image. The determination may occur in a variety of ways by examining the color and intensity characteristics of an image. After the analysis, a determination is received from the image analysis system of whether the image is a not found image or a true image.

Auto classifying images as 'image not available' images

A simulation may be performed to assess availability of a service in the event of various types of failures. A specification may describe a behavior to be induced on a machine, and a formula under which availability is to be measured. A controller processes the specification and dispatches a request to induce the behavior to a machine on which the behavior is to be induced. An agent on that machine may look up a routine in a simulation library and may use the routine to induce the behavior. Data, such as performance counter values, are collected before, during, and/or after occurrence of the behavior, and are transmitted back to the controller. A report generator applies the formula contained in the specification to the data received to calculate the availability metric, and produces a report containing that metric.

Failure simulation and availability report on same

A system or method receives a request to generate a test token. The request identifies a token template that contains information regarding the token to be generated. The system or method identifies the information contained in the token template and generates the requested token based on the information contained in the token template. The generated token may be a defective token.

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Manish Mittal