-
公开(公告)号：US11704325B2
公开(公告)日：2023-07-18
申请号：US17812984
申请日：2022-07-15
发明人： Lawrence Manning , Rahul Mehta , Daniel Erenrich , Guillem Palou Visa , Roger Hu , Xavier Falco , Rowan Gilmore , Eli Bingham , Jason Prestinario , Yifei Huang , Daniel Fernandez , Jeremy Elser , Clayton Sader , Rahul Agarwal , Matthew Elkherj , Nicholas Latourette , Aleksandr Zamoshchin
IPC分类号： G06F16/00 , G06F16/2457 , G06F16/35 , G06F16/9535 , G06F16/28 , G06F18/23
CPC分类号： G06F16/24578 , G06F16/285 , G06F16/35 , G06F16/9535 , G06F18/23
摘要： Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
-
公开(公告)号：US10025834B2
公开(公告)日：2018-07-17
申请号：US14306147
申请日：2014-06-16
发明人： Feridun Arda Kara , Eli Bingham , John Garrod , Daniel Erenrich , Anirvan Mukherjee , Ted Mabrey , Andrew Ash , Zachary Bush , Allen Cai , Winnie Chai , Greg Cohan , Chris Dorsey , William Dwyer , Gilad Gray , Sean Kelley , Dennis Kwon , Chris Lewis , Greg Martin , Parvathy Menon , Brian Ngo , Asli Ozyar , Mike Reilly , Jacob Scott , Ankit Shankar , Matt Sills , Spencer Stamats , Geoff Stowe , Samir Talwar , Engin Ural , Patricio Jones Velez , Holt Wilkins , Diane Wu , Drausin Wulsin , Di Wu , Yu-Hsin Joyce Chen , Baris Kaya
CPC分类号： G06F16/248 , G06F16/26 , G06F16/285 , G06Q10/0639
摘要： Systems and methods are provided for analyzing entity performance. In one implementation, a method is provided that includes recognizing an identifier associated with an entity and accessing a data structure comprising information associated with a plurality of interactions. The method also comprises identifying one or more interactions of the plurality of interactions based on the recognized identifier. The method further comprises processing the information of the identified interactions to analyze a performance of the entity and providing the processed information to display the performance of the entity on a user interface.
-
公开(公告)号：US09852144B2
公开(公告)日：2017-12-26
申请号：US15446917
申请日：2017-03-01
发明人： Geoffrey Stowe , Chris Fischer , Paul George , Eli Bingham , Rosco Hill
CPC分类号： G06F17/30153 , G06F11/2025 , G06F17/00 , G06F17/30067 , G06F17/30091 , G06F17/30106 , G06F17/30129 , G06F17/30371 , G06F17/30528 , G06F17/30554 , G06F17/30569 , G06F17/30705 , G06F17/30867 , G06F17/30955
摘要： A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.
-
公开(公告)号：US20220374454A1
公开(公告)日：2022-11-24
申请号：US17812984
申请日：2022-07-15
发明人： Lawrence Manning , Rahul Mehta , Daniel Erenrich , Guillem Palou Visa , Roger Hu , Xavier Falco , Rowan Gilmore , Eli Bingham , Jason Prestinario , Yifei Huang , Daniel Fernandez , Jeremy Elser , Clayton Sader , Rahul Agarwal , Matthew Elkherj , Nicholas Latourette , Aleksandr Zamoshchin
摘要： Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
-
5.发明申请公开(公告)号：US20190079937A1
公开(公告)日：2019-03-14
申请号：US16189040
申请日：2018-11-13
发明人： Lawrence Manning , Rahul Mehta , Daniel Erenrich , Guillem Palou Visa , Roger Hu , Xavier Falco , Rowan Gilmore , Eli Bingham , Jason Prestinario , Yifei Huang , Daniel Fernandez , Jeremy Elser , Clayton Sader , Rahul Agarwal , Matthew Elkherj , Nicholas Latourette , Aleksandr Zamoshchin
IPC分类号： G06F17/30
摘要： Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
-
公开(公告)号：US09734217B2
公开(公告)日：2017-08-15
申请号：US14306138
申请日：2014-06-16
发明人： Feridun Arda Kara , Eli Bingham , John Garrod , Daniel Erenrich , Anirvan Mukherjee , Ted Mabrey , Andrew Ash , Zachary Bush , Allen Cai , Winnie Chai , Greg Cohan , Chris Dorsey , William Dwyer , Gilad Gray , Sean Kelley , Dennis Kwon , Chris Lewis , Greg Martin , Parvathy Menon , Brian Ngo , Asli Ozyar , Mike Reilly , Jacob Scott , Ankit Shankar , Matt Sills , Spencer Stamats , Geoff Stowe , Samir Talwar , Engin Ural , P J Valez , Holt Wilkins , Diane Wu , Drausin Wulsin , Di Wu , Joyce Yu-Hsin Chen , Bar Kaya
CPC分类号： G06F17/30554 , G06F17/30572 , G06F17/30598 , G06Q10/0639
摘要： Systems and methods are provided for analyzing entity performance. In one implementation, a method is provided that includes receiving a request with one or more filter selections and accessing a data structure comprising a plurality of categories of information showing interactions associated with multiple entities. The method also comprises identifying a set of categories of the plurality of categories within the data structure based on the one or more filter selections. The method further comprises processing the information of the identified categories to analyze a performance of one or more entities of the multiple entities in accordance with the one or more filter selections and providing the processed information to display the performance of the one or more entities on a user interface.
-
公开(公告)号：US20170177606A1
公开(公告)日：2017-06-22
申请号：US15446917
申请日：2017-03-01
发明人： Geoffrey Stowe , Chris Fischer , Paul George , Eli Bingham , Rosco Hill
IPC分类号： G06F17/30
CPC分类号： G06F17/30153 , G06F11/2025 , G06F17/00 , G06F17/30067 , G06F17/30091 , G06F17/30106 , G06F17/30129 , G06F17/30371 , G06F17/30528 , G06F17/30554 , G06F17/30569 , G06F17/30705 , G06F17/30867 , G06F17/30955
摘要： A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.
-
8.发明公开公开(公告)号：US20240320227A1
公开(公告)日：2024-09-26
申请号：US18731699
申请日：2024-06-03
发明人： Lawrence Manning , Rahul Mehta , Daniel Erenrich , Guillem Palou Visa , Roger Hu , Xavier Falco , Rowan Gilmore , Eli Bingham , Jason Prestinario , Yifei Huang , Daniel Fernandez , Jeremy Elser , Clayton Sader , Rahul Agarwal , Matthew Elkherj , Nicholas Latourette , Aleksandr Zamoshchin
IPC分类号： G06F16/2457 , G06F16/28 , G06F16/35 , G06F16/9535 , G06F18/23
CPC分类号： G06F16/24578 , G06F16/285 , G06F16/35 , G06F16/9535 , G06F18/23
摘要： Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
-
公开(公告)号：US12038933B2
公开(公告)日：2024-07-16
申请号：US18325616
申请日：2023-05-30
发明人： Lawrence Manning , Rahul Mehta , Daniel Erenrich , Guillem Palou Visa , Roger Hu , Xavier Falco , Rowan Gilmore , Eli Bingham , Jason Prestinario , Yifei Huang , Daniel Fernandez , Jeremy Elser , Clayton Sader , Rahul Agarwal , Matthew Elkherj , Nicholas Latourette , Aleksandr Zamoshchin
IPC分类号： G06F16/00 , G06F16/2457 , G06F16/28 , G06F16/35 , G06F16/9535 , G06F18/23
CPC分类号： G06F16/24578 , G06F16/285 , G06F16/35 , G06F16/9535 , G06F18/23
摘要： Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
-
公开(公告)号：US20190384747A1
公开(公告)日：2019-12-19
申请号：US16548803
申请日：2019-08-22
发明人： Geoffrey Stowe , Chris Fischer , Paul George , Eli Bingham , Rosco Hill
IPC分类号： G06F16/174 , G06F11/20 , G06F17/00 , G06F16/2457 , G06F16/9535 , G06F16/23 , G06F16/901 , G06F16/25 , G06F16/248 , G06F16/14 , G06F16/35 , G06F16/17 , G06F16/13 , G06F16/10
摘要： A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.
-
-
-
-
-
-
-
-
-
搜索结果
23 条记录 (耗时 0.024 秒)
