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公开(公告)号：US11790679B2
公开(公告)日：2023-10-17
申请号：US17898402
申请日：2022-08-29
发明人： Lokesh Bhatnagar , Himanshu Sharad Bhatt , Manoj Bhokardole , Gabriella P. Fitzgerald , Vinit Jain , Chetan Lohani , Shachindra Pandey , Gunjan Panwar , Shourya Roy , Di Xu
IPC分类号： G06K9/68 , G06V30/40 , G06F16/23 , G06F40/216 , G06F40/242 , G06V30/418 , G06V30/416 , G06V30/262 , G06V10/75 , G06V30/10
CPC分类号： G06V30/40 , G06F16/2365 , G06F40/216 , G06F40/242 , G06V10/75 , G06V30/268 , G06V30/416 , G06V30/418 , G06V30/10
摘要： A system provides an end-to-end solution for invoice processing which includes reading files (such as pdfs and images), extracting key relevant information from the files, organizing the relevant information in a structured template as a key-value pair, and comparing files based on the similarities between different file fields to identify potential duplicate files.
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公开(公告)号：US11450129B2
公开(公告)日：2022-09-20
申请号：US17066747
申请日：2020-10-09
发明人： Lokesh Bhatnagar , Himanshu Sharad Bhatt , Manoj Bhokardole , Gabriella P. Fitzgerald , Vinit Jain , Chetan Lohani , Shachindra Pandey , Gunjan Panwar , Shourya Roy , Di Xu
IPC分类号： G06K9/68 , G06V30/418 , G06F16/23 , G06F40/216 , G06F40/242 , G06V30/416 , G06V30/10
摘要： A system provides an end-to-end solution for invoice processing which includes reading invoices (both pdfs and images), extracting key relevant information from the face of invoices, organizing the relevant information in a structured template as a key-value pair, and comparing invoices based on the similarities between different invoice fields to identify potential duplicate invoices.
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公开(公告)号：US20210248149A1
公开(公告)日：2021-08-12
申请号：US17160889
申请日：2021-01-28
发明人： Arpan Somani , Salil Rajeev Joshi , Shourya Roy
IPC分类号： G06F16/2457 , G06N20/20 , G06F16/22 , G06F40/284 , G06F40/30
摘要： At least some embodiments are directed to an entity matching detection system. The entity matching detection system includes a latent similarity identification machine learning model that receives one or more data records and generates a final similarity score indicative of a latent similarity between the one or more data records and a second data record. The entity matching detection system can identify lexical and semantic similarities between attribute values and can analyze and compute similarity scores for direct-linked attribute values and cross-linked attribute values extracted from different data records.
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公开(公告)号：US20210027054A1
公开(公告)日：2021-01-28
申请号：US17066747
申请日：2020-10-09
发明人： Lokesh Bhatnagar , Himanshu Sharad Bhatt , Manoj Bhokardole , Gabriella P. Fitzgerald , Vinit Jain , Chetan Lohani , Shachindra Pandey , Gunjan Panwar , Shourya Roy , Di Xu
IPC分类号： G06K9/00 , G06F16/23 , G06F40/242 , G06F40/216
摘要： A system provides an end-to-end solution for invoice processing which includes reading invoices (both pdfs and images), extracting key relevant information from the face of invoices, organizing the relevant information in a structured template as a key-value pair, and comparing invoices based on the similarities between different invoice fields to identify potential duplicate invoices.
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公开(公告)号：US11971912B2
公开(公告)日：2024-04-30
申请号：US18136229
申请日：2023-04-18
发明人： Priya Radhakrishnan , Shourya Roy
CPC分类号： G06F16/313 , G06F16/3335 , G06F16/35 , G06F16/36 , G06F40/30 , H04L51/21
摘要： At least some embodiments are directed to a system to compute uniform structured summarization of customer chats. In at least some embodiments, the system may operate a processor and receive a corpus of chats between customers and customer service representatives of an enterprise. Grouping the corpus of chats into subgroup task types and then extracting chat keywords and chat related words for each subgroup task type. Generating an expandable template data structure for each subgroup task type. Processing at least one chat to extract chat utterances and chat snippets ranking the chat utterances and chat snippets. Populating the expandable template data structure based on rankings to generate a chat summary data structure.
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公开(公告)号：US11899676B2
公开(公告)日：2024-02-13
申请号：US18079106
申请日：2022-12-12
发明人： Arpan Somani , Salil Rajeev Joshi , Shourya Roy
IPC分类号： G06F16/2457 , G06N20/20 , G06F40/30 , G06F16/22 , G06F40/284
CPC分类号： G06F16/24578 , G06F16/2255 , G06F40/284 , G06F40/30 , G06N20/20
摘要： At least some embodiments are directed to an entity matching detection system. The entity matching detection system includes a latent similarity identification machine learning model that receives one or more data records and generates a final similarity score indicative of a latent similarity between the one or more data records and a second data record. The entity matching detection system can identify lexical and semantic similarities between attribute values and can analyze and compute similarity scores for direct-linked attribute values and cross-linked attribute values extracted from different data records.
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公开(公告)号：US11861206B1
公开(公告)日：2024-01-02
申请号：US17160843
申请日：2021-01-28
发明人： Lakshman Chaitanya , Arindam Chatterjee , Pratap Singh Singh Rathore , Shourya Roy , Nitish Sharma , Swatee Singh , Mohammad Torkzahrani
IPC分类号： G06F3/06
CPC分类号： G06F3/0652 , G06F3/0608 , G06F3/0659 , G06F3/0673
摘要： Disclosed are various embodiments for garbage collection for object-based storage systems. A first set of objects stored by an object storage service that have been accessed within a previously defined date range is identified. Then, a second set of objects stored by the object storage service is identified based at least in part on a relationship to one or more objects in the first set of objects. Next, a third set of objects stored by the object storage service that have been created prior to a predefined date is identified. Then, a subset of objects which are members of the third set of objects and not members of the first set of objects or the second set of objects is identified. Finally, a retention action is performed on individual members of the subset of objects based at least in part on a retention policy.
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公开(公告)号：US20230252058A1
公开(公告)日：2023-08-10
申请号：US18136229
申请日：2023-04-18
发明人： Priya Radhakrishnan , Shourya Roy
CPC分类号： G06F16/313 , G06F40/30 , G06F16/3335 , G06F16/35 , G06F16/36 , H04L51/21
摘要： At least some embodiments are directed to a system to compute uniform structured summarization of customer chats. In at least some embodiments, the system may operate a processor and receive a corpus of chats between customers and customer service representatives of an enterprise. Grouping the corpus of chats into subgroup task types and then extracting chat keywords and chat related words for each subgroup task type. Generating an expandable template data structure for each subgroup task type. Processing at least one chat to extract chat utterances and chat snippets ranking the chat utterances and chat snippets. Populating the expandable template data structure based on rankings to generate a chat summary data structure.
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公开(公告)号：US11657076B2
公开(公告)日：2023-05-23
申请号：US17205415
申请日：2021-03-18
发明人： Priya Radhakrishnan , Shourya Roy
CPC分类号： G06F16/313 , G06F16/3335 , G06F16/35 , G06F16/36 , G06F40/30 , H04L51/21
摘要： At least some embodiments are directed to a system to compute uniform structured summarization of customer chats. In at least some embodiments, the system may operate a processor and receive a corpus of chats between customers and customer service representatives of an enterprise. Grouping the corpus of chats into subgroup task types and then extracting chat keywords and chat related words for each subgroup task type. Generating an expandable template data structures for each subgroup task type. Processing at least one chat to extract chat utterances and chat snippets ranking the chat utterances and chat snippets. Populating the expandable template data structure based on rankings to generate a chat summary data structure.
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公开(公告)号：US11526523B2
公开(公告)日：2022-12-13
申请号：US17160889
申请日：2021-01-28
发明人： Arpan Somani , Salil Rajeev Joshi , Shourya Roy
IPC分类号： G06F16/2457 , G06N20/20 , G06F40/30 , G06F16/22 , G06F40/284
摘要： At least some embodiments are directed to an entity matching detection system. The entity matching detection system includes a latent similarity identification machine learning model that receives one or more data records and generates a final similarity score indicative of a latent similarity between the one or more data records and a second data record. The entity matching detection system can identify lexical and semantic similarities between attribute values and can analyze and compute similarity scores for direct-linked attribute values and cross-linked attribute values extracted from different data records.
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