AI/ML/NLP¶
Definition:
Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages and, in particular, concerned with programming computers to fruitfully process large natural language corpora. Challenges in Natural Language Processing frequently involve natural language understanding, natural language generation (frequently from formal, machine-readable logical forms), connecting language and machine perception, managing human-computer dialog systems, or some combination thereof.
Syntax¶
- https://en.wikipedia.org/wiki/Lemmatisation
- https://en.wikipedia.org/wiki/Morphology_(linguistics)
- https://en.wikipedia.org/wiki/Part-of-speech_tagging
- https://en.wikipedia.org/wiki/Parsing
- https://en.wikipedia.org/wiki/Sentence_boundary_disambiguation
- https://en.wikipedia.org/wiki/Stemming
- https://en.wikipedia.org/wiki/Text_segmentation#Word_segmentation
Semantics¶
- https://en.wikipedia.org/wiki/Lexical_semantics
- https://en.wikipedia.org/wiki/Machine_translation
- https://en.wikipedia.org/wiki/Named-entity_recognition
- https://en.wikipedia.org/wiki/Natural_language_generation
- https://en.wikipedia.org/wiki/Natural_language_understanding
- https://en.wikipedia.org/wiki/Optical_character_recognition
- https://en.wikipedia.org/wiki/Question_answering
- https://en.wikipedia.org/wiki/Textual_entailment
- https://en.wikipedia.org/wiki/Relationship_extraction
- https://en.wikipedia.org/wiki/Sentiment_analysis
- https://en.wikipedia.org/wiki/Topic_segmentation
- https://en.wikipedia.org/wiki/Word_sense_disambiguation
Discourse¶
Research Papers¶
- “Classifying Movie Scripts by Genre with a MEMM Using NLP-Based Features” (Alex Blackstock, Matt Spitz)
- “SceneMaker: Automatic Visualisation of Screenplays” (Eva Hanser, Paul Mc Kevitt, Tom Lunney, Joan Condell)
- “Speaker identification from film dialogues” (Kundu, A., Das, D., & Bandyopadhyay, S.)
- “Predicting Box Office from the Screenplay: An Empirical Model” (Starling David Hunter, Susan Smith, Saba Singh)
- “Exploiting Structure and Conventions of Movie Scripts for Information Retrieval and Text Mining” (Jhala, A)
- “Scene Boundary Detection from Movie Dialogue: A Genetic Algorithm Approach” (Amitava Kundu, Dipankar Das, Sivaji Bandyopadhyay)
- “Early prediction of a film’s box office success using natural language processing techniques and machine learning” (Sean O’Driscoll)
- “From Storyline to Box Office: A New Approach for Green-Lighting Movie Scripts” (Eliashberg, Hui and Zhang)
- “An Annotated Corpus of Film Dialogue for Learning and Characterizing Character Style” (Walker, M. A., Lin)
- “Gender-Distinguishing Features in Film Dialogue” (Alexandra Schofield, Leo Mehr, CLFL 2016)
- “Assessing Box Office Performance Using Movie Scripts: A Kernel-based Approach” (Jehoshua Eliashberg, Sam K. Hui, Z. John Zhang)
- “Pre-production forecasting of movie revenues with a dynamic artificial neural network” (M. Ghiassi, David Lio, Brian Moon)
- “Parsing Screenplays for Extracting Social Networks from Movies” ( Agarwal, A., Balasubramanian, S., Zheng, J., & Dash, S)