Microsoft Technology Licensing, LLC

Computenext, Inc.

Munirathnam Srikanth

Tarek Najm

Arungunram Chandrasekaran Surendran

Viswanath Vadlamani

Phani Vaddadi

Abhinai Srivastava

Rajeev Prasad

Steve Jamieson

Mahbubul Alam Ali

Prasanth Pulavarthi

Kevin Dougan

Sriram Subramanian

John Midgley

Sundar Kannan

Pieces of hardware on which pieces of software are executed are configured to organize computing resources from different computing resource providers so as to facilitate their discovery. A catalog, which stores instances of cloud computing resources and their providers, and a knowledge base, which stores types of computing resources including rules which reveal their discovery, are formed by the software. A curating method is performed to enable semantic search including searching for cloud computing resources that in combination cooperate to satisfy a workload or a task in addition to having a simple computational function. Semantic indexing is performed to facilitate the semantic search.

Dynamically organizing cloud computing resources to facilitate discovery

Hardware and software are configured to select and provision computing resources from heterogeneous on-demand computing environments through the framework of a layered, federated on-demand computing ecology of computing resource providers, users, and federation servers. These pieces of hardware and software include a mechanism for defining and managing the life cycle of different resource types; a mechanism for extending document-centric protocols to support computing resources as first order objects; a mechanism for routing messages to computing resources; federation topologies; and a mechanism for federation servers to access and use computing resources from providers controlled by other federation servers.

Federating computing resources across the web

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 contextual queries are provided. The system includes a search engine to receive user queries and contexts, a query understanding component to generate a semantic representation of the query, and a data source command generator to transform the semantic representation into commands for multiple data sources. The data source command generator is connected to the query understanding component. The data source command generator selects data source commands based on lexical information associated with each data source.

Contextual queries

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

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

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.

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Redmond, WA, United States of America

Munirathnam Srikanth