Extracting location context from transcripts

Extracting location context from transcripts: a comparison of ELMo and TF-IDF

Happel, David (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Pattern Recognition and Bioinformatics)

Tax, D.M.J. (mentor)
Loog, M. (mentor)
Viering, T.J. (mentor)
Makrodimitris, S. (mentor)
Naseri Jahfari, A. (mentor)

Delft University of Technology

Computer Science and Engineering

CSE3000 Research Project

2020-06-22

Using transcripts of the TV-series FRIENDS, this paper explores the problem of predicting the location in which a sentence was said. The research focuses on using feature extraction on the sentences, and training a logistic regression model on those features. Specifically looking at the differences in performance between using ELMo and TF-IDF for this feature extraction, achieving an accuracy rate of 58\% and 67\% respectively on a binary classification. The paper also explores the effect of several data cleaning techniques on the results.

Git repository containing the source code used in the paper - https://github.com/David-Happel/scene-location-NLP

Natural Language Processing
Text Classification
Word embedding
TF-IDF
ELMo

http://resolver.tudelft.nl/uuid:ad4e3624-4f39-4a64-a678-c232e3f8d7da

Student theses

bachelor thesis

© 2020 David Happel