CSCI 4330/6330: Artificial Intelligence (AI) and the Web

 

 

Instructor:

Prashant Doshi

Office: 418 Boyd GSRC

Ph. No.: 583-0827, Email: pdoshi@cs.uga.edu

 

Course Objectives:

·       To explore and study the AI techniques, systems, and concepts relevant to the WWW

·       To understand the different ways the WWW is being used

·       Develop the art of preparing and delivering fluid, concise, and effective talks and presentations

 

Course Topics:

·         Intelligent information retrieval

       –  Web data mining and clustering, link analysis, graph   mining, text summarization, and the role of natural language processing techniques 

·         Intelligent Web interfaces

       –  User modeling, and Web personalization

·         Semantic Web

       – knowledge representation using logic, theorem proving, trust, and social networking

·         Ontologies

       – reconciliation (clustering, mapping, and merging), and automatic population using machine learning

·         Web services

       – modeling using logics, intelligent discovery and negotiation, and automatic composition

·         Web processes

       – composition and choreography, fault-tolerant and adaptive processes using probabilistic models

·         Single and multi-agent frameworks for the Web

 

References:

There is one required textbook for this course:

 

AI: A Modern Approach, 2nd Edition

By Stuart Russell and Peter Norvig

This textbook is also available in the reserved section of the Science library for 2 hours at a time.

 

The following textbooks will be very useful for reference:

 

Service-Oriented Computing, by Muninder Singh and Michael Huhns, Wiley

 

A Semantic Web Primer, by Antoniou, Grigoris and Frank van Harmelen. MIT Press

 

 

Course Structure:

Teaching

Paper presentations

Scribe duties

Individual project in consultation with the instructor

 

Course Schedule:

This is an approximate schedule and is subject to change:

 

First 10 weeks

Teaching

Middle of semester

Midterm Exam

First round:

Paper presentations

 

Project proposal presentations

Second round:

Paper presentations

Last 2 weeks

Final project demonstrations

   

Grade Allocations:

Final letter grades will depend on class standing

Midterm Exam

Research paper presentations:   

Scribe duties:                             

Project proposal presentation:

Final project presentation:  

In-class participation and Attendance:

:                                                        

25%

30%

10%

10%

15%

10%

 

Course Policy:

The work you submit and present must be your own. Plagiarism and other forms of academic dishonesty will be handled within the guidelines of the Student Handbook. The usual penalty for academic dishonesty is loss of credit for the assignment in question; however, stronger measures may be taken when conditions warrant.