Ravi Kondadadi

Ravi Kondadadi
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Main area of research
Natural language & AI

Ravi Kondadadi is a Principal research scientist at Nuance Communications. He was previously a senior researcher scientist at Thomson Reuters from 2005-2013 and worked as a researcher at Humanizing Technologies from 2002-2005. Ravi received his Masters degree in Computer science from University of Memphis in 2001. His current research focuses on Information Extraction and machine learning, particularly in the areas of deep learning and domain adaptation.

Selected articles

GenNext: A consolidated domain adaptable NLG system

We introduce GenNext, an NLG system designed specifically to adapt quickly and easily to different domains. Given a domain corpus of historical texts, GenNext allows

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A statistical NLG framework for aggregated planning and realization

We present a hybrid natural language generation (NLG) system that consolidates macro and micro planning and surface realization tasks into one statistical learning process. Our

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Domain adaptable semantic clustering in statistical nlg

We present a hybrid natural language generation system that utilizes Discourse Representation Structures (DRSs) for statistically learning syntactic templates from a given domain of discourse

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A flexible table parsing approach

Relational data is often encoded in tables. Tables are easy to read by humans, but difficult to interpret automatically. In cases where table layout cues

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Named entity recognition and resolution in legal text, semantic processing legal texts

Named entities in text are persons, places, companies, etc. that are explicitly mentioned in text using proper nouns. The process of finding named entities in

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