Dr.-Ing. Sagar Sunkle

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Dr. Sagar Sunkle is a senior scientist at Tata Research Development and Design Centre, a premier innovation centre of Tata Consultancy Services. His current research interest is using natural language processing and machine learning techniques for information extraction. His recent work has been on scalable extraction of information from highly noisy data in banking and financial services and related domains. He is also working on legal text comprehension for a more rigorous formal compliance checking in industry setting. His previous work involved using model-driven techniques to help enterprises in decision making, particularly enabling enterprises for regulatory compliance. He has be...

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Toward Better Mapping between Regulations and Operational Details of Enterprises Using Vocabularies and Semantic Similarity

Há 8 anos • 172 Visualizações

Dr.-Ing. Sagar Sunkle

Apresentações

Toward innovative model based enterprise IT outsourcing (NGEBIS CAISE 2013)

Analyzing enterprise models using enterprise architecture-based ontology (MODELS 2013 Presentation)

Intentional modeling for problem solving in enterprise architecture (ICEIS 2013 Presentation)

Visual Modeling Editor and Ontology API-based Analysis for Decision Making in Enterprises- Experience and Way Ahead

Incorporating Directives into Enterprise TO-BE Architecture

Toward Structured Simulation of Enterprise Models

Toward Structured Simulation of What-If Analyses for Enterprise

Practical Goal Modeling for Enterprise ChangeContext: A Problem Statement

Solving Semantic Disparity and Explanation Problems in Regulatory Compliance

Toward a holistic method for regulatory change management

Explanation of Proofs of Regulatory (Non-)Compliance Using Semantic Vocabularies

Model-Driven Regulatory Compliance: A Case Study of “Know Your Customer” Regulations

Documentos

Toward Better Mapping between Regulations and Operational Details of Enterprises Using Vocabularies and Semantic Similarity

Gostaram

Enterprise information extraction: recent developments and open challenges

Knowledge-driven Implicit Information Extraction

WDC Service Summaries - Jan 2015

NIPS2007: structured prediction

Томми Яаккола «Масштабирование структурных предсказаний»

Lecture 5: Structured Prediction

Diving into Machine Learning with Rob Craft, Group Product Manager at Google!

Machine creativity TED Talk 2.0

Alphago Tech talk

From Lookup to Learning: Search as a Long-term Activity – ECIR 2011

Machine Learning for Search at LinkedIn

Learning to Generate Pseudo-code from Source Code using Statistical Machine Translation

Dependency Parsing

10 Reasons Why Successful Leaders Are Keeping a Journal

From Semantic Parsing to Reasoning

Concept net150529

Advanced Hadoop Tuning and Optimization - Hadoop Consulting

Probabilistic Ontology: Representation and Modeling Methodology

What Is A Business Model

Lift11 Presentation

Describe and Improve your Business Model