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Braja Gopal Patra
Researcher at University of Texas Health Science Center at Houston
Publications - 42
Citations - 623
Braja Gopal Patra is an academic researcher from University of Texas Health Science Center at Houston. The author has contributed to research in topics: Mood & Sentiment analysis. The author has an hindex of 12, co-authored 36 publications receiving 461 citations. Previous affiliations of Braja Gopal Patra include Jadavpur University & Cornell University.
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Sentiment Analysis of Code-Mixed Indian Languages: An Overview of SAIL_Code-Mixed Shared Task @ICON-2017
TL;DR: An overview of the shared task on sentiment analysis of code-mixed data pairs of Hindi-English and Bengali-English collected from the different social media platform is presented.
Book ChapterDOI
Shared Task on Sentiment Analysis in Indian Languages SAIL Tweets - An Overview
TL;DR: This is the first attempt to sentiment analysis task in tweets for three Indian languages namely Bengali, Hindi and Tamil, and the main objective was to classify the tweets into positive, negative, and neutral polarity.
Journal ArticleDOI
Extracting social determinants of health from electronic health records using natural language processing: a systematic review.
Braja Gopal Patra,Mohit Manoj Sharma,Veer Vekaria,Prakash Adekkanattu,Olga V. Patterson,Olga V. Patterson,Benjamin S. Glicksberg,Lauren Lepow,Euijung Ryu,Joanna M. Biernacka,Al'ona Furmanchuk,Thomas J. George,William R. Hogan,Yonghui Wu,Xi Yang,Jian-Guo Bian,Myrna M. Weissman,Priya Wickramaratne,J. John Mann,Mark Olfson,Thomas R. Campion,Mark G. Weiner,Jyotishman Pathak +22 more
TL;DR: A systematic review of state-of-the-art NLP approaches and tools that focus on identifying and extracting social determinants of health (SDoH) data from unstructured clinical text in EHRs is presented in this article.
Journal ArticleDOI
A content-based dataset recommendation system for researchers-a case study on Gene Expression Omnibus (GEO) repository.
TL;DR: This work adopts an information retrieval (IR) paradigm for dataset recommendation that hypothesizes that two fundamental differences exist between dataset recommendation and PubMed-style biomedical IR beyond the corpus, and implementation is implemented using a non-parametric clustering technique.
Book ChapterDOI
Unsupervised Approach to Hindi Music Mood Classification
TL;DR: In the present task, an unsupervised classifier for Hindi music mood classification is built using different audio related features like rhythm, timber and intensity.