Yahoo! Inc.

Microsoft Technology Licensing, LLC

Kevin Bartz

Benjamin Rey

Jack Wilson Stokes, Iii

Rosie Jones

David Gregory Grant

Silviu C Calinoiu

Ryan S Kivett

Shaji Sebastian

Gretchen L Loihle

Vijay Murthi

Techniques for determining similarity between error reports received by an error reporting service. An error report may be compared to other previously-received error reports to determine similarity and facilitate diagnosing and resolving an error that generated the error report. In some implementations, the similarity may be determined by comparing frames included in a callstack of an error report to frames included in callstacks in other error reports to determine an edit distance between the callstacks, which may be based on the number and type of frame differences between callstacks. Each type of change may be weighted differently when determining the edit distance. Additionally or alternatively, the comparison may be performed by comparing a type of error, process names, and/or exception codes for the errors contained in the error reports. The similarity may be expressed as a probability that two error reports were generated as a result of a same error.

Similarity detection for error reports

The present disclosure is directed to systems and methods for determining semantically related terms based on sequences of search queries. Generally, a semantically related term tool examines search logs to associate search queries with a user submitting the search query. The semantically related term tool establishes a plurality of sequences of search queries, each sequence of search queries comprising one or more search queries associated with a common user and relating to a common concept. The semantically related term tool receives one or more seed terms and determines one or more terms related to the received seed terms based on the established plurality of sequences of search queries.

System and method for determining semantically related terms based on sequences of search queries

The present invention relates to systems and methods for identifying one or more queries related to a given query. The method of the present invention comprises receiving a query written according to one or more writing systems of a language with multiple writing systems. A candidate set of queries written according to one or more writing systems of the language with multiple writing systems is identified. A score is calculated for the one or more queries in the candidate set indicating the similarity of the one or more queries with respect to the query received.

System and method for identifying related queries for languages with multiple writing systems

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Cambridge, MA, United States of America

Kevin Bartz