Tata Consultancy Services Limited

Kamlesh Mhashilkar

Mahesh M Kshirsagar

Nihar Ranjan Sahoo

Devraj Goulikar

Santosh Kumar Mohanty

Sonam Yashpal Sharma

Abhay Sodani

Aparna Joshi

Sanjeev Manchanda

Saurabh Das

Srikar Chilakamarri

Shivani Nigam

Shriram Pillai

Divya Vasudevan

Vamsee Krishna Kodali

Ajeet Phansalkar

Rajdeep Sarkar

Pushkar Kurhekar

This disclosure relates generally to method and system for extracting contextual information from a knowledge base. The method receives a user query comprising a request to extract contextual information from the user query. Further, the user query is analyzed based on a plurality of predefined parameters to determine sufficiency of information comprised in the user query. The received user query identifies relevant sources of the structured data, the unstructured data or the semi-structured data storage repositories. The user query is processed using a fine grain approach, where a dictionary of one or more keywords with weights are created through the domain ontology builder from the one or more knowledge articles. Furthermore, an appropriate contextual information related to the user query is extracted using the fine grain approach, based on the knowledge articles associated with the trained knowledge base comprising information required by the user query extracted from the knowledge articles.

Method and system for extracting contextual information from a knowledge base

The problem of ever-increasing huge volume of unstructured data, mainly documents, and within that the scanned documents, needs to have a solution to expedite the overall turnaround time in document centric business processing. Majority of these documents often do not strictly follow a specific format or a template, and creating a generic OCR solution, which would work on any kind of document format is needed to enhance overall efficacy of processes. Embodiments of the present disclosure provide system and method that extract tabular and text information from scanned documents. More specifically, method and system are provided to extract user filled tabular data, textual information, selected radio-buttons and checked checkboxes, stamps, barcodes from scanned copies of any filled form with or without any template being pre-defined or without any prior knowledge about format of input forms. The system converts extracted information in a structured form for further for analytics and reporting.

System and method for automated information extraction from scanned documents

With the scale of information available today along with the existing diverse channels of communication, manual processing of information is becoming a challenge and companies across industries are under tremendous pressure to lower transactional costs. Artificial Intelligence based automation of business transactions has seen regulatory hurdles due to probabilistic nature of the outcome. The main challenge lies in processing of transactions with unstructured information. Systems and methods of the present disclosure uses deterministic as well as probabilistic approaches to maximize accuracy. The larger use of deterministic approach with configurable components and ontologies helps to improvise accuracy, precision and reduce recall. The probabilistic approach is used when there is absence of quality information or less information for learning. Also, confidence indicators are provided at attribute level of data being processed and at each decision level.

Automated cognitive processing of source agnostic data

A method and a system for managing enterprise data are provided. The system comprises a processor and a memory coupled to the processor. The memory comprises a definition module defining a Data Management Architecture (DMA). Further, the DMA comprises at least one of an enterprise portal, an enterprise model, at least one adaptor, and a set of metrics. The enterprise portal comprises a set of service tools. The set of service tools is configured to perform a set of services on the data. The enterprise model is configured to analyze an enterprise process to create and modify enterprise metadata of the data originating from the enterprise process. Further, the adapter is configured to communicate with a data source associated with the enterprise process for extracting the enterprise metadata from the data source. Furthermore, the set of metrics may represent an analysis of the data.

System and method for managing enterprise data

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Mumbai, India

Kamlesh Mhashilkar