公开(公告)号：US20210182493A1

公开(公告)日：2021-06-17

申请号：US16823584

申请日：2020-03-19

Applicant: Tata Consultancy Services Limited

Inventor： Lipika DEY ,  Ishan VERMA ,  Saumya BHADANI ,  Mohammad SHAKIR

IPC: G06F40/295 ,  G06F40/258 ,  G06F40/205 ,  G06F40/253 ,  H04L29/06 ,  G06N20/00 ,  G06F16/38 ,  G06F16/33

Abstract: With the proliferation of data and documents available on the internet and other information sources, analysis of adverse events poses a serious technical challenge on account of associated data volume and variety. This disclosure relates generally to identification and profiling of adverse events. By receiving a set of articles from a plurality of data sources and utilizing a series of Natural Language Processors, NLP techniques are employed to identify implicit and explicit adverse events. Entity statistics and sentiment extraction and analysis is performed. An ontology based adverse event identification framework is proposed for identification and profiling of implicit adverse event. An attention based bi-directional long short term memory network for adverse event identification and classification is proposed.

公开(公告)号：US20150019513A1

公开(公告)日：2015-01-15

申请号：US14328172

申请日：2014-07-10

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Lipika DEY ,  Ishan VERMA ,  Arpit KHURDIYA ,  Diwakar MAHAJAN ,  Gautam SHROFF

IPC: G06F17/30

CPC classification number: G06F17/30613 ,  G06F17/30156 ,  G06Q10/10

Abstract: The present subject matter relates to analysis of time-series data based on world events derived from unstructured content. According to one embodiment, a method comprises obtaining event information corresponding to at least one world event from unstructured content obtained from a plurality of data sources. The event information includes at least time of occurrence of the world event, time of termination of the world event, and at least one entity associated with the world event. Further, the method comprises retrieving time-series data pertaining to the entity associated with the world event from a time-series data repository. Based on the event information and the time-series data, the world event is aligned and correlated with at least one time-series event to identify at least one pattern indicative of cause-effect relationship amongst the world event and the time-series event.

Abstract translation: 本主题涉及基于从非结构化内容导出的世界事件的时间序列数据的分析。 根据一个实施例，一种方法包括从从多个数据源获得的非结构化内容获得对应于至少一个世界事件的事件信息。 事件信息至少包括世界事件的发生时间，世界事件终止的时间，以及与世界事件相关联的至少一个实体。 此外，该方法包括从时间序列数据库中检索与世界事件相关联的实体有关的时间序列数据。 基于事件信息和时间序列数据，世界事件被对准并与至少一个时间序列事件相关联，以识别指示世界事件与时间序列事件之间的因果关系的至少一个模式。

公开(公告)号：US20230079455A1

公开(公告)日：2023-03-16

申请号：US17732816

申请日：2022-04-29

Applicant: Tata Consultancy Services Limited

Inventor： Tirthankar DASGUPTA ,  Suyash SANGWAN ,  Tushar GOEL ,  Lipika DEY ,  Akshara RAI ,  Mohammad SHAKIR ,  Abir NASKAR ,  Ishan VERMA ,  Aninda SUKLA

IPC: G06F16/34 ,  G06F16/35

Abstract: Conventionally, text summarization has been rule-based method and neural network based which required large dataset for training and the summary delivered had to be assessed by user in terms of relevancy. System and method are provided by present disclosure that generate causal insight summaries wherein event of importance is detected, and it is determined why event is relevant to a user. Text description is processed for named entities recognition, polarities of sentences identified, extraction of causal effects sentences (CES) and causal relationship identification in text segments which correspond to impacting events. Named entities are then role labeled. A score is computed for named entities, polarities of sentences, causal effects sentences, causal relationships, and the impacting events. A causal insight summary is generated with overall polarity being computed/determined. A customized causal insight summary is delivered to target users based on user preferences associated with specific named entities and impacting events.