Microsoft Technology Licensing, LLC

Viswanath Vadlamani

Tarek Najm

Arungunram Chandrasekaran Surendran

Abhinai Srivastava

Phani Vaddadi

Munirathnam Srikanth

Rajeev Prasad

Egor Nikitin

Alexander Kochis

Jon Milo Elliott

Miller Thomas Abel

John Clavin

Kamran Rajabi Zargahi

John Bruno

Joseph Futty

Steve Tullis

Mohammad Mushtaque Silat

Mahbubul Alam Ali

Prasanth Pulavarthi

Eric P Gilmore

Najm Tarek

Eric Schoonover

John Midgley

Phani K Vaddadi

A request for a digital license associated with a software product is received from a device. The request includes a user ID of a user of the device, with the digital license having been generated in response to a request to activate the software product with a product key. A check is made as to whether a digital license bound to the user ID is available, and also whether the digital license can be returned to the device in accordance with the terms of the digital license. The digital license is returned if the digital license can be returned to the device in accordance with the terms (regardless of whether the device is a same device from which the product key was activated), and otherwise is not returned. The digital license can be removed from the device in accordance with the terms of the digital license.

Availability of permission models in roaming environments

The present disclosure describes a meta-application framework that enables data to be associated with a class of applications called a meta-application. A meta-application entity may store attributes in common across multiple platforms. A platform entity may store attributes in common across multiple devices and/or operating systems. A device entity may be comprised by a particular set of hardware features and an operating system entity may be comprised of a particular set of software feature. Data associated with the meta-application framework may be accessed directly via data manipulation operations or alternatively by application operations via an application programming interface or via the aforementioned data manipulation operations. Applications may then identify application specific behavior at the appropriate level of detail.

Meta-application framework

Search result re-ranking is provided by employing a concept graph from a metabase. When a search query is received, a query context of the search query is analyzed to identify dominant concepts for the search query. The dominant concepts are expanded by identifying the dominant concepts within a concept graph and identifying additional concepts having a strong relationship with the dominant concepts within the concept graph. A set of search results for the search query is analyzed to determine strength of relationship of each search result to the expanded concepts. The search results are re-ranked based on the strength of relationship of each search result to the expanded concepts and the strength of relationship of each expanded concept to the dominant concepts.

Re-ranking search results based on lexical and ontological concepts

A procedural inference system is described herein that infers procedural knowledge from various data sources to help a user complete one or more tasks for which the data sources provide information. The system understands users' queries, identifies a task at hand, provides recommendations on the steps to take and the agents to use based on a knowledge base of tasks and agents, and provides the fabric to determine which different agents can work together to help the user accomplish a task. Tasks can be started on one device and completed on another seamlessly. Users are able to finish complex, multi-step tasks efficiently, without trial and error or data reentry. Thus, the procedural inference system provides a generalized framework that helps users to complete tasks using already available data and does not ask each data provider to invest in infrastructure to build dedicated task information systems.

Inferring procedural knowledge from data sources

Systems, methods, and computer-storage media for generating lateral concepts are provided. The system includes a search engine to receive user queries, a storage to store content and its associated categories, and a lateral concept generator. The lateral concept generator is connected to both the search engine and storage. The lateral concept generator selects lateral concepts from categories associated with the content based on similarity scores for the stored content.

Generating and presenting lateral concepts

An application sequence may be composed in response to a user query. The application sequence may be based upon user data accessed by the application concierge service. Each application within the personalized chain of applications may request and receive data from the application concierge service about the other applications within the chain.

Application store concierge

Review and filtering of search results is facilitated by providing additional types of results beyond links to existing documents can be provided in addition to or in place of links to existing documents. These additional results can facilitate modifying a search request to filter out unwanted documents. The additional results, when in the form of content display objects and/or application display objects, can also provide the user with varying levels of information detail. In some preferred embodiments, an ontology based knowledge base can be leveraged in order to facilitate providing and filtering the results.

Progressive filtering of search results

Electronic documents are analyzed to identify assertions, which are inverted to generate questions that may be answered by the assertions. A document or a corpus of electronic documents may be analyzed to identify entities and relationships among entities within the text of the document(s). Assertions are identified based on the entities and relationships among the entities. Each assertion represents a fact about an entity, and a group of assertions represents a summary of the document or document corpus. The assertions are inverted to generate questions that may be answered by the assertions. The questions may be further analyzed to identify relevant concepts and topics and to cluster the questions around the concepts and topics. A combined graph may also be generated that facilitates traversal among topics, concepts, questions, assertions, document summaries, and documents.

Ontological categorization of question concepts from document summaries

A table of contents is generated for search results in response to a search query by identifying semantic concepts as topics for inclusion within the table of contents. When a search query is received, a search is performed to identify search results. The search results are compared to an ontology of topics to identify relevant topics. Additionally, search results are compared to an ontology of partial topics to identify relevant partial topics, which are named. Independent key-phrases are further generated from search results and identified as key-phrase topics. The identified topics, named partial topics, and key-phrase topics are ranked, and topics are selected for inclusion within a table of contents. A search results page is returned in response to the search query that includes search results and the generated table of contents.

Semantic table of contents for search results

Advertisements are selected for presentation on search result pages and web pages based on phrases generated from lateral concepts and topics identified for the search result pages and web pages. A search query or an indication of a web page is received for which advertisements are to be provided. Lateral concepts and topics are identified based on the search query or content of the web page. The lateral concepts and topics are used as phrases for selecting advertisements from an advertisement inventory. Selected advertisements are provided for presentation on a search results page in response to a search query or on a web page initially identified.

Semantic advertising selection from lateral concepts and topics

Display screen with a user interface

Records, including data for a virtual catalog, may be received from a number of sources. Each of the received records may be validated and a determination may be made as to whether one or more previously-received records matches the received record. When two or more records are determined to be matching records, a composite object may be created and information from the two or more records may be included in the composite object. If the matching records include conflicting information, then previously-defined rules may be applied to determine which items of the conflicting information have precedence over other items of the conflicting information. A virtual catalog may be created from the received records and the created composite object based on customized attributes.

Growing community of inventors

Sammamish, WA, United States of America

Viswanath Vadlamani