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公开(公告)号：US10216838B1
公开(公告)日：2019-02-26
申请号：US15394610
申请日：2016-12-29
Applicant: Google Inc.
Inventor： Luis Garcia Pueyo , Vanja Josifovski , Amitabh Saikia , Jie Yang , Mike Bendersky , Srinidhi Viswanatha , Marc-Allen Cartright
Abstract: 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.
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公开(公告)号：US10216837B1
公开(公告)日：2019-02-26
申请号：US14584905
申请日：2014-12-29
Applicant: Google Inc.
Inventor： Amitabh Saikia , Marc-Allen Cartright , Luis Garcia Pueyo , Vanja Josifovski , Jie Yang , Mike Bendersky , MyLinh Yang
Abstract: 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.
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公开(公告)号：US09756073B2
公开(公告)日：2017-09-05
申请号：US15416632
申请日：2017-01-26
Applicant: Google Inc.
Inventor： Mike Bendersky , Luis Garcia Pueyo , Kashyap Ramesh Puranik , Amitabh Saikia , Jie Yang , Marc-Allen Cartright
CPC classification number: H04L63/1483 , H04L63/0254 , H04L63/1425 , H04L63/20
Abstract: Methods, apparatus, systems, and computer-readable media are provided for determining whether communications are attempts at phishing. In various implementations, a potentially-deceptive communication may be matched to one or more templates of a plurality of templates. Each template may represent content shared among a cluster of communications sent by a legitimate entity. In various implementations, it may be determined that an address associated with the communication is not affiliated with one or more legitimate entities associated with the one or more matched templates. In various implementations, the communication may be classified as a phishing attempt based on the determining.
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公开(公告)号：US09596265B2
公开(公告)日：2017-03-14
申请号：US14711407
申请日：2015-05-13
Applicant: Google Inc.
Inventor： Mike Bendersky , Luis Garcia Pueyo , Kashyap Ramesh Puranik , Amitabh Saikia , Jie Yang , Marc-Allen Cartright
IPC: H04L29/06
CPC classification number: H04L63/1483 , H04L63/0254 , H04L63/1425 , H04L63/20
Abstract: Methods, apparatus, systems, and computer-readable media are provided for determining whether communications are attempts at phishing. In various implementations, a potentially-deceptive communication may be matched to one or more templates of a plurality of templates. Each template may represent content shared among a cluster of communications sent by a trustworthy entity. In various implementations, it may be determined that an address associated with the communication is not affiliated with one or more trustworthy entities associated with the one or more matched templates. In various implementations, the communication may be classified as a phishing attempt based on the determining.
Abstract translation: 提供了方法，装置，系统和计算机可读介质，用于确定通信是否是网络钓鱼的尝试。 在各种实现中，潜在的欺骗性通信可以与多个模板中的一个或多个模板相匹配。 每个模板可以表示由可信赖实体发送的通信集群之间共享的内容。 在各种实现中，可以确定与通信相关联的地址不隶属于与一个或多个匹配模板相关联的一个或多个可信赖实体。 在各种实现中，可以基于确定将通信分类为网络钓鱼尝试。
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公开(公告)号：US10360537B1
公开(公告)日：2019-07-23
申请号：US15484933
申请日：2017-04-11
Applicant: Google Inc.
Inventor： Mike Bendersky , Maureen Heymans , Jinan Lou , Jie Yang , MyLinh Yang , Amitabh Saikia , Marc-Allen Cartright , Vanja Josifovski , Hui Tan , Luis Garcia Pueyo
IPC: G06F17/30 , G06Q10/10 , G06F16/248 , G06F16/9535 , H04W4/029
Abstract: 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.
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Patent Agency Ranking
公开(公告)号：US20180144042A1
公开(公告)日：2018-05-24
申请号：US15360939
申请日：2016-11-23
Applicant: Google Inc.
Inventor： Ying Sheng , Yifeng Lu , Jing Xie , Jie Yang , Luis Garcia Pueyo , Jinan Lou , James Wendt
CPC classification number: G06F16/285 , G06F16/93 , G06F17/243 , G06F17/248 , G06N20/00 , G06N20/20 , G06Q10/10
Abstract: Techniques are described herein for automatically generating data extraction templates for structured documents (e.g., B2C emails, invoices, bills, invitations, etc.), and for assigning classifications to those data extraction templates to streamline data extraction from subsequent structured documents. In various implementations, a data extraction template generated from a cluster of structured documents that share fixed content may be identified. Features of the cluster of structured documents may be applied as input to extraction machine learning model(s) trained to provide location(s) of transient field(s) in structured documents, to determine location(s) of transient field(s) in the cluster of structured documents. An association between the data extraction template and the determined transient field location(s) may be stored. Based on the association, data point(s) may be extracted from a given structured document of a user that shares fixed content with the cluster of structured documents. The extracted data point(s) may be surfaced to the user.
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公开(公告)号：US09652530B1
公开(公告)日：2017-05-16
申请号：US14470416
申请日：2014-08-27
Applicant: Google Inc.
Inventor： Mike Bendersky , Maureen Heymans , Jinan Lou , Jie Yang , MyLinh Yang , Amitabh Saikia , Marc-Allen Cartright , Vanja Josifovski , Hui Tan , Luis Garcia Pueyo
IPC: G06F17/30
CPC classification number: G06F17/30705 , G06F17/30923
Abstract: 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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公开(公告)号：US20160314184A1
公开(公告)日：2016-10-27
申请号：US14697342
申请日：2015-04-27
Applicant: Google Inc.
Inventor： Mike Bendersky , Jie Yang , Amitabh Saikia , Marc-Allen Cartright , Sujith Ravi , Balint Miklos , Ivo Krka , Vanja Josifovski , James Wendt , Luis Garcia Pueyo
IPC: G06F17/30
CPC classification number: G06F16/35 , G06Q10/107
Abstract: Methods, apparatus, systems, and computer-readable media are provided for classifying, or “labeling,” documents such as emails en masse based on association with a cluster/template. In various implementations, a corpus of documents may be grouped into a plurality of disjoint clusters of documents based on one or more shared content attributes. A classification distribution associated with a first cluster of the plurality of clusters may be determined based on classifications assigned to individual documents of the first cluster. A classification distribution associated with a second cluster of the plurality of clusters may then be determined based at least in part on the classification distribution associated with the first cluster and a relationship between the first and second clusters.
Abstract translation: 提供了方法，装置，系统和计算机可读介质，用于基于与集群/模板的关联来整合或“标记”诸如电子邮件的文档。 在各种实现中，基于一个或多个共享内容属性，文档的语料库可以被分组成多个不相交的文档簇。 可以基于分配给第一集群的单个文档的分类来确定与多个集群中的第一集群相关联的分类分发。 然后可以至少部分地基于与第一集群相关联的分类分布和第一和第二集群之间的关系来确定与多个集群中的第二集群相关联的分类分发。
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公开(公告)号：US10540610B1
公开(公告)日：2020-01-21
申请号：US15139807
申请日：2016-04-27
Applicant: Google Inc.
Inventor： Jie Yang , Amr Ahmed , Luis Garcia Pueyo , Mike Bendersky , Amitabh Saikia , Marc-Allen Cartright , Marc Alexander Najork , MyLinh Yang , Hui Tan , Weinan Zhang , Vanja Josifovski , Alexander J. Smola
Abstract: 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).
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公开(公告)号：US09785705B1
公开(公告)日：2017-10-10
申请号：US14516122
申请日：2014-10-16
Applicant: Google Inc.
Inventor： Marc-Allen Cartright , Luis Garcia Pueyo , Vanja Josifovski , Amitabh Saikia , Jie Yang , Mike Bendersky , MyLinh Yang
IPC: G06F17/30
CPC classification number: G06F17/30705
Abstract: 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.
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