Intelligent Information Retrieval

DS 575 / IS 575
Winter 2006

Syllabus

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Course Material

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Intelligent Information Retrieval

Course Syllabus

Instructor:

Bamshad Mobasher
Email: mobasher@cs.depaul.edu
Office: Loop Campus, CTI Building, Room 833
Phone: (312) 362-5174
Office Hours: Tue. 4:00-5:30, Wed. 4:30-5:45 PM (or by appointment)

Textbooks and Reading Material:

Finding Out About: A Cognitive Perspective on Search Engine Technology and the WWW, by Richard K. Belew, Cambridge University Press, 2001.
Information Retrieval,(online book), by C. J. van Rijsbergen, (available online here).
Research and Reference Articles (provided in class or online).

Prerequisites:

CSC 373 and 384; or instructor permission.

Grading Policy:

The final grade will be determined based on the following components:

Assignments = 65%
Final Project = 35%

The general grading scheme will be based on a curve, but the grade cutoffs will be no higher than: A = 90-100%, B = 80-89%, C = 65-79%, D = 50-64%, F = 0-49%. Within each grading range +/- grading will be used. At the end of the quarter, some adjustments may be made based on overall class performance as well as signs of individual effort.

Assignments:

There will be 4-5 assignments involving problems related to concepts and techniques discussed in class, as well as experiments with various tools or systems. Unless otherwise specified, these assignments must be done individually. Generally, late assignments will be penalized 10% per day (with weekends counting as one day). No late assignments will be accepted after the "latest submission date" (specified in class for each assignment). All assignments must be submitted electronically (see the Assignments Section for more detail).

Course Project

The final project for the class can be either an implementation project or a written project. The implementation projects would involve the design and implementation of an information retrieval, filtering, or integration system (or a specific part of a system). The written projects must involve a detailed study, survey, and evaluation of one or more topics or systems related to information retrieval and filtering. Written projects must be done individually, while implementation may be done individually or in groups of up to 3 people (depending the size and the complexity of the project). Each group or individual must submit a specific project proposal to be approved no later than February 9. A list of project ideas and some additional details regarding the projects are available in the Project Section. The due date for the final project is Monday, March 13.

Tentative List of Topics

Topics

Overview of IR Systems, Historical Perspectives, Basic Evaluation.
Document Representation: Statisitcal Characteristics of Text, Basic Query Processing.
Data Structure and File Organization for IR.
Automatic Indexing and Indexing Models.
Retrieval Models: Similarity Measures and Ranking, Boolean Matching, Vector Space Models, Probabilistic Models
Search and Filtering Techniques: Relevance Feedback, User Profiles, Collaborative Filtering
Document and Term Clustering, Document Categorization.
IR Systems and the WWW, Heterogeneous Information Sources, Intelligent Web Agents.
Web Mining and Its Applications