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This course is a graduate level introduction to automatic discourse processing.
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English
English [CC]
FREE
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Description
The emphasis will be on methods and models that have applicability to natural language and speech processing.
The class will cover the following topics: discourse structure, models of coherence and cohesion, plan recognition algorithms, and text segmentation. We will study symbolic as well as machine learning methods for discourse analysis. We will also discuss the use of these methods in a variety of applications ranging from dialogue systems to automatic essay writing.
This subject qualifies as an Artificial Intelligence and Applications concentration subject.
Course content
- Introduction Unlimited
- Topic Segmentation: Agreement, Evaluation, Automatic Text Segmentation Unlimited
- Topic Segmentation (cont.): Hierarchical Text Segmentation, Meeting Segmentation Unlimited
- Cohesion and Local Coherence: Lexical Chains, Centering Theory; Applications to Automated Essay Scoring Unlimited
- Automatic Reference Resolution Unlimited
- Automatic Reference Resolution and Reference Generation Unlimited
- Generation of Referring Expressions Unlimited
- Domain-dependent Models of Text Structure Unlimited
- Rhetorical Structure Theory Unlimited
- Discourse Structure in Text Summarization; Alignment Unlimited
- Temporal Ordering in Discourse Unlimited
- Intentions and the Structure of Discourse Unlimited
- Studies of Dialogues; Taxonomy of Speech Acts Unlimited
- Automatic Interpretation of Dialogue Acts Unlimited
- Learning Dialogue Strategies via Reinforcement Learning Unlimited
- MIT Dialogue Systems Unlimited
- Dialogue Systems Unlimited
- Plan Recognition Unlimited
- Evaluation for Discourse Processing Unlimited
- Discourse in Psycholinguistics Unlimited
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Instructor
Massachusetts Institute of Technology
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