Yahoo! Inc.

International Business Machines Corporation

Google Inc.

Excalibur Ip, LLC

Yahoo! Overture

Vanja Josifovski

Marcus Felipe Fontoura

Andrei Z Broder

Jie Yang

Luis Garcia Pueyo

Mike Bendersky

Amitabh Saikia

Marc-Allen Cartright

Peter Martin Schwarz

MyLinh Yang

Martin Breining

Edison Lao Ting

Evgeniy Gabrilovich

Lance Alan Riedel

Deepayan Chakrabarti

Hui Tan

Andrew Stephen Tomkins

Shanmugasundaram Ravikumar

Deepak Agarwal

Bo Pang

Maureen Heymans

Christopher Olston

Jinan Lou

Donald Metzler

Srinidhi Viswanatha

Deepak K Agrawal

Reiner Kraft

Guy Maring Lohman

Peter Haas

Marc Alexander Najork

Robert Hall

Benjamin Clay Reed

Beverly Yang

Alexander Johannes Smola

Alexander Shraer

Anirban Dasgupta

Chun Zhang

Yejin Choi

Amr Ahmed

Maxim Gurevich

Hila Becker

Peter Ciccolo

Petros Drineas

Boulos Harb

Michael William Mahoney

Pratik Mukhopadhyay

Dejan Diklic

Weinan Zhang

Eugene K Shekita

Mauricio Riguette Mediano

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, and computer-readable media are provided for generating and applying data extraction templates. In various implementations, a corpus of structured communications such as emails may be grouped into clusters based on one or more similarities between the structured communications. A set of structural paths may be identified from structured communications of a particular cluster. One or more structural paths of the set may be classified as transient wherein a count of occurrences of one or more associated segments of text across the particular cluster satisfies a criterion. One or more transient paths may be assigned a semantic data type and/or a confidentiality designation based on various signals. A data extraction template may be generated to extract, from subsequent structured communications, segments of text associated with transient (and in some cases, non-confidential) structural paths.

Generating and applying 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

A method and apparatus are provided for better web ad matching by combining relevance with consumer click feedback. In one example, the method includes receiving a query page, extracting features from the query page, re-weighting the query page, evaluating the query page in light of each ad in order to score each ad and pick substantially best ad matches of the indexed ads, and returning the substantially best ad matches to the consumer computer.

Method and apparatus for web ad matching

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.

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

Provided are techniques for processing a query. A query is received, wherein the query is formed by one or more paths, and wherein each path includes one or more steps. A hierarchical document including one or more document nodes is received. While processing the query and traversing the hierarchical document, one or more extraction entries are constructed, wherein each extraction entry includes a step instance match candidate identifying a document node and a step instance ancestor path for the document node, and one or more tuples are constructed using the one or more extraction entries by associating the step instance match candidate from one of the one or more extraction entries with the step instance match candidate from at least one of the one or more other extraction entries.

Query evaluation using ancestor information

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.

Various methods and apparatuses are provided which may be implemented using one or more computing devices within a networked computing environment to employ publish-subscribe techniques to associate subscriber encoded data files with a set of publisher encoded data files.

Publish-subscribe based methods and apparatuses for associating data files

A system and a method are provided for using external sources (e.g., landing pages) for sponsored search ad selection. In one example, the system identifies one or more regions of an external source. The one or more regions are relevant to a query. The external source includes a source that includes relevant data that is usable for augmenting an ad selection process. The system extracts one or more features from the one or more regions. The system determines which of the one or more features are relevant for item indexing. The system then augments an item selection process by using the one or more features that are relevant for item indexing.

Using external sources for sponsored search AD selection

A computer-implemented method is disclosed for determining a type of landing page to which to transfer web searchers that enter a particular query, the method comprising: classifying a landing page as one of a plurality of landing page classes with a trained classifier of a computer based on textual content of the landing page; determining, by the computer, characteristics of one or more query to be associated with the landing page; and choosing, with the computer, whether to retain or to change classification of the landing page to be associated with the one or more query based on relative average conversion rates of advertisements on a plurality of manually-classified landing pages when associated with the characteristics of the one or more query.

Context transfer in search advertising

Methods and systems are provided that may be used to determine a probability of whether a visitor to a web document is likely to click on a web advertisement. An exemplary method may include detecting one or more features in a web document. One or more expert statistical models to which the web document belongs may be determined and associated weightings may be determined based, at least in part, on the one or more features detected. A click-through-rate probability for a web advertisement to be placed on the web document may be estimated based on the one or more expert statistical models.

Method and system for quantifying user interactions with web advertisements

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Los Gatos, CA, United States of America

Vanja Josifovski