Introduction to Knowledge and Knowledge Management Concepts, Knowledge Modeling, Introduction to Information Retrieval, Information Retrieval Models, Retrieval Evaluation, Query Languages and Operations, Document Processing, Search Techniques.

Semester:

August

Rationale:

It has become recognized that knowledge of products, processes, management, and technologies is one of the most important assets of the modern corporation. To gain maximum benefit, this resource must be effectively managed. This includes knowledge capture, storage, and dissemination. Since knowledge is often embodied in textual documents, information storage and retrieval form a central part of the techniques for knowledge management. Information retrieval has also become one of the most important technologies used in conjunction with the Internet, in the form of search engines.

Catalog Description:

Introduction to Knowledge and Knowledge Management Concepts, Knowledge Modeling, Introduction to Information Retrieval, Information Retrieval Models, Retrieval Evaluation, Query Languages and Operations, Document Processing, Search Techniques.

Credits:

3(3-0)

Prerequisite:

None

Course Outline:

Introduction to Knowledge and Knowledge Management Concepts

1. Knowledge in Organizations
2. Knowledge Processes

Knowledge Modeling

1. Ontologies
2. Structures, Concepts, and Relationships
3. Organization Modeling
4. Communication and Dynamics Modeling
5. Knowledge Transfer
6. Total Knowledge Management

Introduction to Information Retrieval

1. Information versus Data Retrieval
2. The User Task
3. Logical View of Documents
4. Information Retrieval in Digital Libraries and the Web

Information Retrieval Models

1. Taxonomy of IR Models
2. Classical IR: Boolean, Vector, Probabilistic
3. Alternative Models: Bayesian Networks, Neural Networks
4. Structured Text Retrieval Models
5. Models for Browsing

Retrieval Evaluation

1. Retrieval Performance Evaluation
2. Reference Collections

Query Languages and Operations

1. Keyword Based Querying
2. Structural Queries
3. Query Expansion
4. Automatic Local and Global Analysis

Document Processing

1. Lexical Analysis
2. Stemming and Stopwords
3. Text Compression

Search Techniques

Textbook:

Lecture Notes.

Reference Books:

T.H. Davenport and L. Prusak:

Working Knowledge, Harvard Business School Press, 2000.

R. Baeza-Yates and B. Ribeiro-Neto:

Modern Information Retrieval, ACM Press, Addison Wesley, 1999.

A. Tiwana:

Knowledge Management Toolkit, The: Practical Techniques for Building a Knowledge Management System, Prentice Hall, 1999.

S.I. Tannenbaum and G.M. Alliger:

Knowledge Management: Clarifying the Key Issues, IHRIM, 2000.

W. Applehans, A. Globe, and G. Laugero:

Managing Knowledge: A Practical Web-Based Approach, Addison-Wesley, 1998.

R. K. Belew:

Finding Out About, Cambridge University Press, 2000.

M.W. Berry and M. Browne:

Understanding Search Engines, Society for Industrial and Applied Mathematics, 1999.

W. Frakes, R. Baeza-Yates:

Information Retrieval: Data Structures and Algorithms, Prentice Hall, 1992.

A. G. Taylor:

The Organization of Information, Libraries Unlimited, 1999.

ACM Special Interest Group on Information Retrieval (SIGIR)

http://www.acm.org/sigir

Grading System:

The final grade will be computed from the following constituent parts mid-semester exam (20%), final exam (40%), assignments/projects (40%). Closed-book examination is used for both mid-semester and final exam.

Instructor:

Dr. Peter Haddawy

Contact us: Olivier Nicole

Last update: Jul 2003