Search Results for author: Rajiv Shah

Found 6 papers, 3 papers with code

Exploring and Learning Suicidal Ideation Connotations on Social Media with Deep Learning

no code implementations WS 2018 Ramit Sawhney, Manch, Prachi a, Puneet Mathur, Rajiv Shah, Raj Singh

The increasing suicide rates amongst youth and its high correlation with suicidal ideation expression on social media warrants a deeper investigation into models for the detection of suicidal intent in text such as tweets to enable prevention.

Classification General Classification +1

Identification of Emergency Blood Donation Request on Twitter

1 code implementation WS 2018 Puneet Mathur, Meghna Ayyar, Sahil Chopra, Simra Shahid, Laiba Mehnaz, Rajiv Shah

Social media-based text mining in healthcare has received special attention in recent times due to the enhanced accessibility of social media sites like Twitter.

Did you offend me? Classification of Offensive Tweets in Hinglish Language

1 code implementation WS 2018 Puneet Mathur, Ramit Sawhney, Meghna Ayyar, Rajiv Shah

The use of code-switched languages (\textit{e. g.}, Hinglish, which is derived by the blending of Hindi with the English language) is getting much popular on Twitter due to their ease of communication in native languages.

Abuse Detection General Classification +2

Detecting Offensive Tweets in Hindi-English Code-Switched Language

no code implementations WS 2018 Puneet Mathur, Rajiv Shah, Ramit Sawhney, Debanjan Mahata

The paper focuses on the classification of offensive tweets written in Hinglish language, which is a portmanteau of the Indic language Hindi with the Roman script.

General Classification Hate Speech Detection +1

Applying Deep Bidirectional LSTM and Mixture Density Network for Basketball Trajectory Prediction

no code implementations19 Aug 2017 Yu Zhao, Rennong Yang, Guillaume Chevalier, Rajiv Shah, Rob Romijnders

In the hit-or-miss classification experiment, the proposed model outperformed other models in terms of the convergence speed and accuracy.

Time Series Trajectory Prediction

Applying Deep Learning to Basketball Trajectories

1 code implementation12 Aug 2016 Rajiv Shah, Rob Romijnders

Using a dataset of over 20, 000 three pointers from NBA SportVu data, the models based simply on sequential positional data outperform a static feature rich machine learning model in predicting whether a three-point shot is successful.

Feature Engineering Sports Analytics

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