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Dec 26, 2024
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CS 6840 - Natural Language Processing
Natural Language Processing (NLP) is a branch of Artificial Intelligence that focuses on the design of computer systems for processing, understanding, or communicating in natural language. This graduate level course covers statistical and machine learning approaches for solving fundamental tasks in NLP, such as language modeling, part of speech tagging, syntactic parsing, word sense disambiguation, semantic role labeling, coreference resolution, and semantic parsing. Students will also learn about major applications of NLP, including information retrieval and web search, information extraction, question answering, machine translation, sentiment analysis, text mining, and speech recognition.
Requisites:
Credit Hours: 3
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:
- Students will be able to build language models for authorship attribution and language detection.
- Students will be able to implement the probabilistic CKY algorithm for unlexicalized syntactic parsing.
- Students will be able to use existing NLP packages to train and evaluate HMMs and CRFs for sequence tagging.
- Students will be able to use machine learning algorithms for word sense disambiguation.
- Students will be able to use statistical and neural techniques for developing language models.
- Students will be able to use Phrase Structure Grammars, Dependency Grammars, and Combinatory Categorial Grammars for syntactic parsing of text.
- Students will be able to apply basic text processing steps such as sentence segmentation, tokenization, and stemming.
- Students will be able to evaluate deterministic and learning-based algorithms for coreference resolution.
- Students will be able to use formal meaning representations based on lambda calculus and first order predicate logic.
- Students will be able to describe the significance of NLP in solving practical problems such as Information Retrieval, Information Extraction, and Question Answering.
- Students will be able to use third party packages to solve natural language processing problems.
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