Google Inc.

MyLinh Yang

Andrew Stephen Tomkins

Shanmugasundaram Ravikumar

Shalini Agarwal

Bo Pang

Mark Yinan Li

Vanja Josifovski

Jie Yang

Luis Garcia Pueyo

Mike Bendersky

Amitabh Saikia

Marc-Allen Cartright

Hui Tan

Maureen Heymans

Jinan Lou

Marc Alexander Najork

Alexander Johannes Smola

Amr Ahmed

Weinan Zhang

Methods and apparatus related to identifying one or more messages sent by a user, identifying two or more contacts that are associated with one or more of the messages, determining a strength of relationship score between identified contacts, and utilizing the strength of relationship scores to provide additional information related to the contacts. A strength of relationship score between a contact and one or more other contacts may be determined based on one or more properties of one or more of the messages. In some implementations, contacts groups may be determined based on the strength of relationship scores. In some implementations, contacts groups may be utilized to disambiguate references to contacts in messages. In some implementations, contacts group may be utilized to provide suggestions to the user of additional contacts of a contacts group that includes the indicated recipient contact of a message.

Determining strength of association between user contacts

Methods and apparatus related to determining an effect on dissemination of information related to an event based on a dynamic confidence level associated with the event. For example, an event and an event confidence level of the event may be determined based on a message of a user. An effect on dissemination of information related to the event may be determined based on the confidence level. A new confidence level may be determined based on additional data associated with the event and the effect on dissemination of information may be adjusted based on the new confidence level. In some implementations, the additional data may be based on a new message that is related to the message, such as a reply to the message.

Determining an effect on dissemination of information related to an event based on a dynamic confidence level associated with the event

Methods, apparatus, and computer-readable media are provided for analyzing a cluster of communications, such as B2C emails, to generate a template for the cluster that defines transient segments and fixed segments of the cluster of communications. More particularly, methods, apparatus, and computer-readable media are provided for generating and/or applying a trained structured machine learning model for a generated template that can be used to determine, for one or more transient segments of subsequent communications, a corresponding probability that a given semantic label is the correct semantic label for extracted content of the transient segment(s).

Generating and applying a trained structured machine learning model for determining a semantic label for content of a transient segment of a communication

Techniques are described herein for generating and applying event data extraction templates. In various implementations, a data extraction template may be applied to structured communications to extract, from each structured communication, event data associated with a transient markup language path indicated in the data extraction template. The data extraction template may include an event-related semantic data type assigned to the transient markup language path and a strength of association between the transient structural path and the event-related semantic data type. Feedback may be obtained concerning event data extracted from one or more of the structured communications. Based on the feedback, the strength of association between the transient markup language path and the event-related semantic data type may be altered. The data extraction template may then be applied to a subsequent structured communication to extract new event data from the structured communication based on the altered strength of association.

Generating and applying event data extraction templates

Methods, apparatus, systems, and computer-readable media are provided for selecting pattern matching segments suitable for electronic communication clustering. A set of pattern matching segments may be identified that match at least one of a corpus of electronic communication addresses. A measure of coverage of each of the set of pattern matching segments across the corpus of electronic communication addresses may be determined. A score associated with each pattern matching segment may be determined based on the measure of coverage and one or more measures of flexibility associated with each of the set of pattern matching segments. One or more of the pattern matching segments may be selected based on the determine scores. A corpus of electronic communications may then be grouped into a plurality of clusters based on a comparison of the one or more selected pattern matching segments to electronic communication addresses associated with the corpus of electronic communications.

Selecting pattern matching segments for electronic communication clustering

Methods and apparatus related to providing additional information related to a vague term in a message. For example, in some implementations, one or more messages sent by a sender and received by one or more recipients may be identified, a vague term in the message may be identified, a user-restricted database may be identified that is associated with the sender or a recipient, and additional information related to the vague term may be determined from the user-restricted database. A vague term is a term which may have multiple meanings and that can be clarified with additional information. In some implementations, user-restricted databases may include additional information that is associated with the user that may be utilized to replace the vague term with a clarified term. In some implementations, a user-restricted database may be utilized to identify additional information in another database that may be utilized to clarify the vague term.

Providing additional information related to a vague term in a message

Methods, apparatus, systems, and computer-readable media are provided for generating and applying data extraction templates. In various implementations, a corpus of plain text communications such as emails may be grouped into clusters based on one or more similarities between the plain text communications. One or more segments of communications of a particular cluster may be classified as transient based on textual pattern matching. One or more other segments of the communications of the particular cluster may be classified as transient based on various criteria. One or more transient segments may be assigned a generic and/or specific semantic data type and/or a confidentiality designation based on various signals. A data extraction template may be generated to extract, from subsequent plain text communications, content associated with transient (and in some cases, non-confidential) segments.

Generating and applying data extraction templates

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for redacting data from a document collection generated for a set of documents that include personal information. The redaction of the data is based in part on a comparison of the document collection to a set of a personal documents of users for which the users have provided explicit approval to use in the processing of the document collection.

Information redaction from document data

Methods and apparatus are described herein for generating and applying event data extraction templates. In various implementations, a set of structural paths may be identified from a corpus of communications. A first structural path of the set of structural paths, associated with a first segment of text, may be classified as transient in response to a determination that a frequency of occurrences of the first segment of text across the corpus satisfies a criterion. Event heuristics may be applied to the communications of the corpus. A determination may be made, based on the applying, that the communications of the corpus are event-related. An event data type may be assigned to the transient structural path based on the applying. An event data extraction template may be generated to extract, from one or more subsequent communications, one or more event-related segments of text associated with the transient structural path.

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Saratoga, CA, United States of America

MyLinh Yang