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1.
公开(公告)号:US20220374769A1
公开(公告)日:2022-11-24
申请号:US17663240
申请日:2022-05-13
Applicant: Tata Consultancy Services Limited
Inventor: AMIT SANGROYA , LOVEKESH VIG , MOULI RASTOGI , CHANDRASEKHAR ANANTARAM
Abstract: Conventionally three main approaches are utilized for explainability of blackbox ML systems: proxy or shadow model approaches, model inspection approaches and data based approaches. Most of the research work on explainability has followed one of the above approaches with each having its own limitations and advantages. Embodiments of the present disclosure provide a method and system for explainable Machine learning (ML) using data and proxy model based hybrid approach to explain outcomes of a ML model. The hybrid approach is based on Local Interpretable Model-agnostic Explanations (LIME) using Formal Concept Analysis (FCA) for structured sampling of instances. The approach combines the benefits of using a data-based approach (FCA) and proxy model-based approach (LIME).
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2.
公开(公告)号:US20220342919A1
公开(公告)日:2022-10-27
申请号:US17753514
申请日:2020-03-04
Applicant: Tata Consultancy Services Limited
Inventor: AMIT SANGROYA , GAUTAM SHROFF , CHANDRASEKHAR ANANTARAM , MRINAL RAWAT , PRATIK SAINI
IPC: G06F16/33 , G06F16/332 , G06F40/20
Abstract: For various applications (for example, a Virtual Assistant), mechanisms that are capable of collecting user queries and generating responses are being used. While such systems handle structured queries well, they struggle to or fail to interpret an unstructured Natural Language (NL) query. The disclosure herein generally relates to data processing, and, more particularly, to a method and a system for generating responses to unstructured Natural Language (NL) queries. The system collects at least one NL query as input at a time, and generates a sketch, where the sketch is a structured representation of the unstructured NL query. Further by processing the sketch, the system generates one or more database queries. The one or more database queries are then used to search in one or more associated databases and to retrieve matching results, which are then used to generate response to the at least one NL query.
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公开(公告)号:US20230109692A1
公开(公告)日:2023-04-13
申请号:US17822722
申请日:2022-08-26
Applicant: Tata Consultancy Services Limited
Inventor: ANUMITA DASGUPTA , INDRAJIT BHATTACHARYA , GIRISH KESHAV PALSHIKAR , PRATIK SAINI , SANGAMESHWAR SURYAKANT PATIL , SOHAM DATTA , PRABIR MALLICK , SAMIRAN PAL , SUNIL KUMAR KOPPARAPU , AISHWARYA CHHABRA , AVINASH KUMAR SINGH , KAUSTUV MUKHERJI , MEGHNA ABHISHEK PANDHARIPANDE , ANIKET PRAMANICK , ARPITA KUNDU , SUBHASISH GHOSH , CHANDRASEKHAR ANANTARAM , ANAND SIVASUBRAMANIAM , GAUTAM SHROFF
Abstract: This disclosure relates generally to method and system for providing assistance to interviewers. Technical interviewing is immensely important for enterprise but requires significant domain expertise and investment of time. The present disclosure aids assists interviewers with a framework via an interview assistant bot. The method initiates an interview session for a job description by selecting a set of qualified candidates resume to be interviewed. Further, the IA bot recommends each interviewer with a set of question and reference answer pairs prior initiating the interview. At each interview step, the IA bot records interview history and recommends interviewer with the revised set of questions. Further, an assessment score is determined for the candidate using the reference answer extracted from a resource corpus. Additionally, statistics about the interview process is generated, such as number and nature of questions asked, and its variation across to identify outliers for corrective actions.
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