Classifying Movie Scripts by Genre with a MEMM Using NLP-Based Features

In this project, we hope to classify movie scripts into genres based on a variety of NLP-related features extracted from the scripts. We devised two evaluation metrics to analyze the performance of two separate classifiers, a Naive Bayes Classifier and a Maximum Entropy Markov Model Classifier. Our two biggest challenges were the inconsistent format of the movie scripts and the multiway classification problem presented by the fact that each movie script is labeled with several genres. Despite these challenges, our classifier performed surprisingly well given our evaluation metrics. We have some doubts, though, about the reliability of these metrics, mainly because of the lack of a larger test corpus.