150 citations · 334 across the 51 of their papers we have counts for
5 papers · 1 filter
Folksonomication: Predicting Tags for Movies from Plot Synopses Using Emotion Flow Encoded Neural Network
Sudipta Kar, Suraj Maharjan, Thamar Solorio
Folksonomy of movies covers a wide range of heterogeneous information about movies, like the genre, plot structure, visual experiences, soundtracks, metadata, and emotional experie…
RiTUAL-UH at TRAC 2018 Shared Task: Aggression Identification
Niloofar Safi Samghabadi, Deepthi Mave, Sudipta Kar +1
This paper presents our system for "TRAC 2018 Shared Task on Aggression Identification". Our best systems for the English dataset use a combination of lexical and semantic features…
UH-PRHLT at SemEval-2016 Task 3: Combining Lexical and Semantic-based Features for Community Question Answering
Marc Franco-Salvador, Sudipta Kar, Thamar Solorio +1
In this work we describe the system built for the three English subtasks of the SemEval 2016 Task 3 by the Department of Computer Science of the University of Houston (UH) and the…
Letting Emotions Flow: Success Prediction by Modeling the Flow of Emotions in Books
Suraj Maharjan, Sudipta Kar, Manuel Montes-y-Gomez +2
Books have the power to make us feel happiness, sadness, pain, surprise, or sorrow. An author's dexterity in the use of these emotions captivates readers and makes it difficult for…
MPST: A Corpus of Movie Plot Synopses with Tags
Sudipta Kar, Suraj Maharjan, A. Pastor López-Monroy +1
Social tagging of movies reveals a wide range of heterogeneous information about movies, like the genre, plot structure, soundtracks, metadata, visual and emotional experiences. Su…