公开(公告)号：US20210224483A1

公开(公告)日：2021-07-22

申请号：US17225589

申请日：2021-04-08

Applicant: Verint Systems Ltd.

Inventor： Daniel Baum ,  Uri Segal ,  Ron Wein ,  Oana Sidi

IPC: G06F40/289 ,  G06F16/36 ,  G06F40/284

Abstract: A method for expanding an initial ontology via processing of communication data, wherein the initial ontology is a structural representation of language elements comprising a set of entities, a set of terms, a set of term-entity associations, a set of entity-association rules, a set of abstract relations, and a set of relation instances. A method for extracting a set of significant phrases and a set of significant phrase co-occurrences from an input set of documents further includes utilizing the terms to identify relations within the training set of communication data, wherein a relation is a pair of terms that appear in proximity to one another.

公开(公告)号：US20170206893A1

公开(公告)日：2017-07-20

申请号：US15473231

申请日：2017-03-29

Applicant: Verint Systems Ltd.

Inventor： Ran Achituv ,  Omer Ziv ,  Roni Romano ,  Ido Shapira ,  Daniel Baum

IPC: G10L15/07 ,  G10L15/01 ,  G10L15/14

Abstract: Methods, systems, and computer readable media for automated transcription model adaptation includes obtaining audio data from a plurality of audio files. The audio data is transcribed to produce at least one audio file transcription which represents a plurality of transcription alternatives for each audio file. Speech analytics are applied to each audio file transcription. A best transcription is selected from the plurality of transcription alternatives for each audio file. Statistics from the selected best transcription are calculated. An adapted model is created from the calculated statistics.

公开(公告)号：US20160217127A1

公开(公告)日：2016-07-28

申请号：US15007699

申请日：2016-01-27

Applicant: Verint Systems Ltd.

Inventor： Uri Segal ,  Oana Sidi ,  Ron Wein ,  Daniel Baum

IPC: G06F17/27

CPC classification number: G06F17/2775 ,  G06F16/367 ,  G06F17/277

Abstract: A method for expanding an initial ontology via processing of communication data, wherein the initial ontology is a structural representation of language elements comprising a set of entities, a set of terms, a set of term-entity associations, a set of entity-association rules, a set of abstract relations, and a set of relation instances. A method for extracting a set of significant phrases and a set of significant phrase co-occurrences from an input set of documents further includes utilizing the terms to identify relations within the training set of communication data, wherein a relation is a pair of terms that appear in proximity to one another.

Abstract translation: 一种用于通过处理通信数据来扩展初始本体的方法，其中初始本体是包括一组实体的语言元素的结构表示，一组术语，一组术语 - 实体关联，一组实体关联规则 ，一组抽象关系，以及一组关系实例。 一种用于从输入文档集中提取一组重要短语和一组重要短语共同出现的方法还包括利用这些术语来识别通信数据训练集内的关系，其中关系是出现的一对术语 彼此接近。