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Damir Cavar is a Natural Language Processing, AI, and Knowledge Representation scientist

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29 June 2017

CSCI-B 659 and LING-715 Semantic Natural Language Processing, NoAI, and Big Knowledge

by Damir Cavar

This fall I am teaching the course:

CSCI-B 659 TOPICS ARTIFICIAL INTELLIGENCE (and LING-L 715 SEMINAR IN COMPUTATIONAL LING) (3 CR)

VT: SEMANTICS AND DISCOURSE

10761 PERM 09:30A-10:45A TR BH 221 Cavar D 8 6 0

(Note: This is not CSCI-B 659/LING-L 645 Topics in Artificial Intelligence/Advanced NLP!)

Topic: Semantic Natural Language Processing, NoAI, and Big Knowledge

The goal of this seminar is to understand theoretical and practical aspects of:

Our goal is to set up a fully functional system by end of the semester.

We did that on two AWS instances. More information about that can be found here:

http://linguistic.technology/

Issues

This is a theoretical and also very practical seminar that includes:

Students from Linguistics and language studies will gain experience with the newest technologies that are underlying applications like Amazon Alexa, Google Assistant, IBM Watson, etc. They will have the opportunity to model linguistic knowledge (lexical, syntactic, semantic, pragmatic) and apply it in high-level technological environments.

Students from Data Science, Computer Science, Engineering, will gain experience with real advanced NLP technologies and methods, open source projects, industry relevant APIs and technologies.

Cognitive Science students will gain experience with modeling of concept nets and knowledge representations, real applications with NLP, machine learning, and AI algorithms.

The course will group students into projects with priorities on modeling linguistic processing and analysis, knowledge representations and graph-based technologies, spoken language interfaces using common SDKs and APIs from Amazon and Google, etc., depending on the students core skills and main interests.

Research Questions

The content of the course can have these special foci, among others:

Resources

For more details consult the Fall 2017 course website.

tags: Graph-DB Alexa "Google Assistant" OWL NLP LFG "Dependency Parser" "Lexical-functional Grammar" textmining "deep parsing" "knowledge graphs"