Tata Consultancy Services Limited

Suyash Sangwan

Lipika Dey

Ishan Verma

Mohammad Shakir

Tirthankar Dasgupta

Abir Naskar

Tushar Goel

Aninda Sukla

Akshara Rai

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.

Systems and methods for generating causal insight summary

Growing community of inventors

Gurgaon, India

Suyash Sangwan