Microsoft Technology Licensing, LLC

Workman Nydegger

Microsoft Corporation

Joshua T Goodman

Robert L Rounthwaite

Gary William Flake

Eric J Horvitz

Oliver Hurst-Hiller

Geoffrey John Hulten

Trenholme J Griffin

William Henry Gates, Iii

Christopher A Meek

Susan Theresa Dumais

David Earl Heckerman

John Carlton Platt

Ramez Naam

Bradly A Brunell

Anoop Gupta

Manav Mishra

Raymond Edward Ozzie

Bryan T Starbuck

Xuedong D Huang

Carl Myers Kadie

Eric David Brill

Kenneth Alan Moss

Nathan D Howell

Surajit J Chaudhuri

John D Mehr

Anthony Paul Penta

Alexander G Gounares

David Maxwell Chickering

Eliot Carleton Gillum

Paul Stephen Rehfuss

Gopalakrishnan Seshadrinathan

Micah C Rupersburg

Robert George Atkinson

Jensen Michael Harris

Eran Megiddo

James M Lyon

Kyle G Peltonen

Roy Williams

Khaja Ehteshamuddin Ahmed

Elissa E Murphy

Wen-tau Yih

Ryan Charles Colvin

Harry Simon Katz

Derek M Hazeur

David E Heckerman

Stephen L Lawler

Richard J Wolf

Srikanth Shoroff

Alexei V Bocharov

Cynthia Dwork

Aaron H Averbuch

Andrew V Goldberg

Kenneth Grey Richards

Daniel Gwozdz

Dane Alexander Glasgow

Michael Victor Ehrenberg

Roderic C Deyo

Dean Alan Slawson

Daniel S Venolia

Jay T Buckingham

Wen-Tau Yih

Donald E Bradford

Kenneth R Aldinger

John R Douceur

Jianfeng Gao

Josh D Benaloh

Ying Li

Ethan Nelson Ray

Robert C Moore

Hsiao-Wuen Hon

Gina Danielle Venolia

Omar H Shahine

Lucretia Henrica Vanderwende

Hisami Suzuki

Elissa E S Murphy

Ewa Dominowska

Robert C J Pengelly

Christopher D Payne

Nina Kang

Ojiakonobi Udezue

Wende E Copfer

Elliott Jeb Haber

Ariel Katz

Yifat Sagiv

John Deurbrouck

Guy Friedel

David Aaron Ward Snelling

Thomas A Leung

Aly Valli

Chun Yu Wong

Paul R Weber

Stephen Lardieri

Manish M Anand

Roderict C Deyo

Vitor Rocha De Carvalho

Kristin D Bromm

Denise D Hui

Matthew S Carr

Carl M Kadie

The subject disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user. Still further yet, a localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. A system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.

Search guided by location and context

Architecture that monitors interaction data (e.g., search queries, query results and click-through rates), and provides users with links to other users that fall into similar categories with respect to the foregoing monitored activities (e.g., providing links to individuals and groups that share common interests and/or profiles). A search engine can be interactively coupled with one or more social networks, and that maps individuals and/or groups within respective social networks to subsets of categories associated with searches. A database stores mapped information which can be continuously updated and reorganized as links within the system mapping become stronger or weaker. The architecture can comprise a social network system that includes a database for mapping search-related information to an entity of a social network, and a search component for processing a search query for search results and returning a link to an entity of a social network based on the search query.

Search engine that identifies and uses social networks in communications, retrieval, and electronic commerce

The subject invention provides for an advanced and robust system and method that facilitates detecting spam. The system and method include components as well as other operations which enhance or promote finding characteristics that are difficult for the spammer to avoid and finding characteristics in non-spam that are difficult for spammers to duplicate. Exemplary characteristics include analyzing character and/or number sequences, strings, and sub-strings, detecting various entropy levels of one or more character sequences, strings and/or sub-strings and analyzing message headers.

Advanced spam detection techniques

Data management in social networks

Described is a technology by which phishing-related data sources are processed into aggregated data and a given site evaluated the aggregated data using a predictive model to automatically determine whether the given site is likely to be a phishing site. The predictive model may be built using machine learning based on training data, e.g., including known phishing sites and/or known non-phishing sites. To determine whether an object corresponding to a site is likely a phishing-related object are described, various criteria are evaluated, including one or more features of the object when evaluated. The determination is output in some way, e.g., made available to a reputation service, used to block access to a site or warn a user before allowing access, and/or used to assist a hand grader in being more efficient in evaluating sites.

Finding phishing sites

Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Machine assisted query formulation

Provided is mechanism for guiding computer searches (e.g., web, Internet, intranet . . . ). Machine learning and reasoning mechanisms are employed together with a search engine to facilitate intelligent guidance of queries and results based on a query and responses to computer generated inquires. Also, disclosed is a mechanism that enables users to validate computer-based information. Users can receive a validity metric associated with computer generated or provided results. Validation systems and methods are disclosed to facilitate determining the results including those that employ humans (e.g., referrals, voting . . . ) and/or automated ways (e.g., source analysis, data mining . . . ).

Intelligently guiding search based on user dialog

Multiple pieces of information can be arranged into a single construct that allows the employee to ascertain information quickly while at her workstation. Selection of information for placement into the construct can employ various statistical models and the like. Selective pieces of information can be masked for a user's construct based upon access rights of the user. Constructs can be configured by a user based on personal preferences as well as by an administrator. Population of metadata upon the construct can be performed automatically through an instruction of the administrator or be overridden by a user request. In addition, various types of synchronization can be implemented between constructs, such that identical or near-identical information is populated upon multiple constructs.

Communication workspace

Architecture for presenting advertisements in realtime in retail establishments. A sensor component includes sensors for collecting information about a customer or group of customers as they move through the store. The sensors can include capability for image processing, audio processing, light sensing, velocity sensing, direction sensing, proximity sensing, face recognition, pose recognition, transaction recognition, and biometric sensing, for example. A customer component analyzes the information and generates a profile about the customer. Advertisements are selected for presentation that target the customers as they walk in proximity of a presentation system of the store. An advertisement component facilitates dynamic presentation of a targeted advertisement to the individual as a function of the profile. The customer component can infer information during analysis using machine learning and reasoning.

Targeted advertising in brick-and-mortar establishments

Providing for generation of a task oriented data structure that can correlate natural language descriptions of computer related tasks to application level commands and functions is described herein. By way of example, a system can include an activity translation component that can receive a natural language description of an application level task. Furthermore, the system can include a language modeling component that can generate the data structure based on an association between the description of the task and at least one application level command utilized in executing the computer related task. Once generated, the data structure can be utilized to automate computer related tasks by input of a human centric description of those tasks. According to further embodiments, machine learning can be employed to train classifiers and heuristic models to optimize task/description relationships and/or tailor such relationships to the needs of particular users.

Providing a task description name space map for the information worker

Content management architecture for a portable wireless device. Caching and fetching techniques are provided to improve content handling for portable devices such as cellular telephones and portable computers. A search component automatically performs searches as a background process, and potentially desired content is received and cached by a content storing component to be available in the future when and if needed, mitigating latency associated with slow download speeds, refresh rates, and other system and/or network impediments. Content from background search results can be trickled into the device as part of the background process so as not to burden system resources for other processes. As part of memory management, aged and/or low priority or low interest content can be selectively removed or archived to increase available cache or memory space, as well as to maintain relevant content within the device. A presentation component facilitates presentation of the pre-stored content.

Architecture for user- and context-specific prefetching and caching of information on portable devices

The subject invention provides for an advanced and robust system and method that facilitates detecting spam. The system and method include components as well as other operations which enhance or promote finding characteristics that are difficult or the spammer to avoid and finding characteristics in non-spam that are difficult for spammers to duplicate. Exemplary characteristics include examining origination features in pairs, analyzing character and/or number sequences, strings, and sub-strings, detecting various entropy levels of one or more character sequences, strings and/or sub-strings as well as analyzing message and/or feature sizes.

The subject disclosure pertains to anonymous network interaction. More specifically, mechanisms are provided to ensure anonymity with respect network interaction such that third parties are unable to determine the source and/or intent of communications. Accordingly, entities may anonymize all outgoing and/or incoming data packets so as to mitigate outside entities from learning about information being sought and/or provided. For example, a user or corporation may employ an anonymizer with respect to web searching so that outside entities are not able to determine what information is attempted to be accessed and by whom.

Anonymous and secure network-based interaction

Growing community of inventors

Redmond, WA, United States of America

Joshua T Goodman