Accenture Global Solutions Limited

Wipro Limited

Chetan Narasimha Yadati

Chung-Sheng Li

Krishna Kummamuru

Guruprasad Dasappa

Surajit Sen

Madhura Shivaram

Swati Tata

Deepak Kumar

Deepak Dalwani

Venkata Ramakrishnap

Mudita Shah

Vivek Chenna

An information request processor analyzes an information request and automatically selects search queries and information sources that are responsive to the information request. Prior reports and portions of browsing history that were generated during the creation of the prior reports are selected based at least on a primary entity included in the information request. The entities extracted from the prior reports using trained Information Extraction (IE) models are mapped to the search terms extracted from the portions of the browsing history in order to identify the successful search queries that provided the information for the prior reports. A report responsive to the information request can be generated either automatically or by receiving user input that validates and rephrases the successful search queries.

Document processing based on proxy logs

An AI-based data processing system analyzes a received information request to generate an interactive visualization including data responsive to the information request. The information request is processed to obtain the primary entity and one or more informational items related to the primary entity. Auxiliary entities and informational items related to the primary entity are identified and searches are executed on a knowledge base and the internet. The results from the searches are analyzed to obtain knowledge nuggets which are included into a selected one of a visualization template to generate the interactive visualization. If it is determined via user interactions with the interactive visualization that an informational gap exists between the information request and the data in the interactive visualization, the interactive visualization can be updated to address the informational gap.

Artificial intelligence based-document processing

System and method for data cleansing are disclosed. The method comprises receiving one or more data records pre-categorized into one or more categories. Identifying at least one concept associated with one or more data records, and grouping, the at least one concept associated with the one or more data records into a plurality of category lists based on the predefined category associated with each of the one or more data records. Determining, one or more intersection sets based on a comparison between each pair of the plurality of category lists, wherein each intersection set comprises a set of one or more common concepts associated with a pair of category lists. The method comprises replacing each of at least one common concept of the set of one or more common concepts associated with each intersection set by a category name based on an occurrence rate of the common concepts.

System and method for data cleansing

In one embodiment, a method for transforming training data to improve data classification is disclosed. The method comprises extracting concepts from a training data set. The method comprises computing frequency of occurrence of each concept in each category and removing concepts from the data records when the frequency of occurrence of a concept in a category is less than a threshold frequency value. Further, the method comprises computing a percentage contribution of each concept of remaining concepts in each category upon removing the concepts and eliminating concepts, from the remaining concepts, contributing equally to each category based on the percentage contribution of each concept to provide a reformed training data set. Further, the method comprises appending a category name to a corresponding data record in the reformed training data set based on a normalized frequency of occurrence of the concept in a category to improve data classification.

Methods and systems for transforming training data to improve data classification

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Bengaluru, India

Chetan Narasimha Yadati