公开(公告)号：US10002159B2

公开(公告)日：2018-06-19

申请号：US14214070

申请日：2014-03-14

Applicant: Infosys Limited

Inventor： John Kuriakose ,  Sai Deepak Tunuguntla

IPC: G06F17/30 ,  G06F17/00

CPC classification number: G06F16/24522

Abstract: The embodiments of the present invention provide a computer-implemented method and system for translating user keywords into semantic queries based on domain vocabulary. The system receives the user keywords and search for the concepts. The concepts are transformed into a connected graph. The user keywords are translated into precise access paths based on the information relationship described in conceptual entity relationship models and then converts these paths into logic based queries. It bridges the semantic gap between user keywords and logic based structured queries. It enables users to interact with the semantic system by articulating the information in a structured query language. It improves the relevance of search results by incorporating semantic technology to drive the mechanics of the search solution.

公开(公告)号：US11334608B2

公开(公告)日：2022-05-17

申请号：US15933151

申请日：2018-03-22

Applicant: Infosys Limited

Inventor： Debanjan Mahata ,  John Kuriakose

IPC: G06F16/33 ,  G06N3/08 ,  G06F16/93 ,  G06F16/901 ,  G06F16/34

Abstract: A system and method combining supervised and unsupervised natural language processing to extract keywords from text in natural language processing, the method includes receiving, through a processor, one or more entities through an input processing unit and converting the one or more entities into a standard document object. Further, parsing the standard document object through a text processing engine into one or more of a sentence and a token and selecting through a candidate identification engine one or more right candidates to be ranked. Further, assigning one or more scores to the one or more right candidates, ranking the one or more right candidates through a graph based ranking engine, creating a connected graph between the ranked one or more right candidates and assigning, through a phrase embedding engine, an edge weight to one or more edges between a right candidate and another right candidate.

公开(公告)号：US20190155944A1

公开(公告)日：2019-05-23

申请号：US15933151

申请日：2018-03-22

Applicant: Infosys Limited

Inventor： Debanjan Mahata ,  John Kuriakose

IPC: G06F17/30 ,  G06N3/08

Abstract: A system and method combining supervised and unsupervised natural language processing to extract keywords from text in natural language processing, the method includes receiving, through a processor, one or more entities through an input processing unit and converting the one or more entities into a standard document object. Further, parsing the standard document object through a text processing engine into one or more of a sentence and a token and selecting through a candidate identification engine one or more right candidates to be ranked. Further, assigning one or more scores to the one or more right candidates, ranking the one or more right candidates through a graph based ranking engine, creating a connected graph between the ranked one or more right candidates and assigning, through a phrase embedding engine, an edge weight to one or more edges between a right candidate and another right candidate.

公开(公告)号：US20180075013A1

公开(公告)日：2018-03-15

申请号：US15473424

申请日：2017-03-29

Applicant: Infosys Limited

Inventor： Abdul Razack ,  Sudipto Dasgupta ,  Mayoor Rao ,  John Kuriakose

IPC: G06F17/27 ,  G06N99/00 ,  G06N5/02 ,  G06F17/30

Abstract: A method and system automates training named entity recognition in natural language processing to build configurable entity definitions includes receiving input documents or entities through an administration module and defining a domain for each entity. Further, one or more entities corresponding to the domain specific entity in the received documents are determined and a training file to one of pick a right parser, extract content and label the entity ambiguity is generated. One or more user actions are collected and maintained at a repository through a knowledge engine. Still further, one or more labelled ambiguous words are predicted and the knowledge engine is updated. Data may be fetched, through a training pipeline execution engine and each entity may be associated with one or more documents based on the fetched data from the document store to build configurable entity definitions.

公开(公告)号：US20140379755A1

公开(公告)日：2014-12-25

申请号：US14214070

申请日：2014-03-14

Applicant: Infosys Limited

Inventor： John Kuriakose ,  Sai Deepak Tunuguntla

IPC: G06F17/30 ,  G06N5/04

CPC classification number: G06F17/3043

Abstract: The embodiments of the present invention provide a computer-implemented method and system for translating user keywords into semantic queries based on domain vocabulary. The system receives the user keywords and search for the concepts. The concepts are transformed into a connected graph. The user keywords are translated into precise access paths based on the information relationship described in conceptual entity relationship models and then converts these paths into logic based queries. It bridges the semantic gap between user keywords and logic based structured queries. It enables users to interact with the semantic system by articulating the information in a structured query language. It improves the relevance of search results by incorporating semantic technology to drive the mechanics of the search solution.

Abstract translation: 本发明的实施例提供了一种用于将用户关键字转换为基于域词汇的语义查询的计算机实现的方法和系统。 系统接收用户关键字并搜索概念。 概念被转换为连接图。 基于概念实体关系模型中描述的信息关系将用户关键字转换为精确的访问路径，然后将这些路径转换为基于逻辑的查询。 它桥接了用户关键字和基于逻辑的结构化查询之间的语义差距。 它使用户能够通过以结构化查询语言表达信息来与语义系统进行交互。 它通过结合语义技术来驱动搜索解决方案的机制来提高搜索结果的相关性。

公开(公告)号：US10558754B2

公开(公告)日：2020-02-11

申请号：US15473424

申请日：2017-03-29

Applicant: Infosys Limited

Inventor： Abdul Razack ,  Sudipto Dasgupta ,  Mayoor Rao ,  John Kuriakose

IPC: G06F17/27 ,  G06N5/02 ,  G06N20/00

Abstract: A method and system automates training named entity recognition in natural language processing to build configurable entity definitions includes receiving input documents or entities through an administration module and defining a domain for each entity. Further, one or more entities corresponding to the domain specific entity in the received documents are determined and a training file to one of pick a right parser, extract content and label the entity ambiguity is generated. One or more user actions are collected and maintained at a repository through a knowledge engine. Still further, one or more labelled ambiguous words are predicted and the knowledge engine is updated. Data may be fetched, through a training pipeline execution engine and each entity may be associated with one or more documents based on the fetched data from the document store to build configurable entity definitions.