Microsoft Technology Licensing, LLC

Wenxuan Gao

Weidong Zhang

Weiqin Ma

Bin Wu

Shaunak Chatterjee

Kapil Laxmikant Surlaker

Bee-Chung Chen

Grace W Tang

Joel Daniel Young

Boyi Chen

David J Stein

Wei Zhuang

Paul Taylor Ogilvie

Amit Chandak

Jimmy Hong

Varnit Agnihotri

Divya Gadde

Ruoyang Wang

Amit Yadav

Yangchun Luo

Yishu Lin

Ke Wu

Priyanka Gariba

The disclosed embodiments provide a system for processing data. During operation, the system obtains a feature configuration for a feature. Next, the system obtains, from the feature configuration, an anchor containing metadata for accessing the feature in an environment. The system then uses one or more attributes of the anchor to retrieve one or more feature values of the feature from the environment. Finally, the system provides the one or more feature values for use with one or more machine-learning models.

Framework for managing features across environments

The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of records from a set of inputs, with each record containing an entity key, a partition key, and one or more attribute-value pairs. Next, the system sorts and indexes the records by the entity key for each partitioned input. The system then processes a query of the records by matching entity key values to the sorted and indexed records for each input partition in the query. Next, the system merges the subset of records with the same entity key values into records, with each merged record containing an entity key field and a single field that includes a list of attribute-value pairs from the subset. Finally, the system outputs the merged records in response to the query.

Efficient merging and filtering of high-volume metrics

Computer-implemented techniques for constructing structured database query language statements from natural language questions are disclosed. In some embodiments, a knowledge graph-based approach is employed to construct a structured database query language statement such as, for example, a Structure Query Language (SQL) statement, from a natural language question. The approach encompasses a domain knowledge graph model and a database schema wiring model. The domain knowledge graph model represents domain-specific knowledge about the underlying database data in the form of a graph having nodes and directed edges between the nodes. The database schema wiring model maps routes in the domain knowledge graph to database schema elements. The techniques allow a natural language interface system to accurately translate domain-specific natural language questions posed by users to structured database query language statements that can be executed against a structured database to answer the natural language question.

Constructing structured database query language statements from natural language questions

Methods, systems, and computer programs are presented for selecting a title for a post of a social network. A method includes operations for identifying a word weight for each word in a corpus based on the relevance of each word, receiving a document that includes several sentences, and assigning to each word in the sentences a tag indicative of a part of speech. Further, the method includes operations for calculating a topic weight for each sentence based on the tags of the words in the sentence, and for calculating a sentence weight for each sentence based on a sum of the word weights of the words in the sentence, the topic weight for the sentence, and a position weight of the sentence within a paragraph. The sentence with the highest sentence weight is selected as the title for the document, and the title is presented with the document to a user.

Title extraction using natural language processing

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Santa Clara, CA, United States of America

Wenxuan Gao