Introduction to Information Retrieval: Concepts, Structures, and Time Perspective
The purpose of this tutorial is to familiarize the audience with the concepts related to the implementation of Information Retrieval Systems (IRSs). Topics to be covered include indexing, document representation, query document matching, underlying file structures, user search practices, similarities and differences of IR and information filtering systems, and performance evaluation. A time frame perspective of IRSs will also be provided.


Clustering for Information Retrieval: Techniques, Applications, and Evaluation
Cluster analysis deals with automating a very human process: classifying objects into groups of similar objects. From the viewpoint of information retrieval systems the objects are the documents that are relevant to the same information need. The purpose of this tutorial is to present a comprehensive overview of the current research on the use of clustering methods for information retrieval. After an introduction to the basic concepts, various clustering algorithms are examined. Their implementation details, application areas, and evaluation methods are provided.

Fazli Can
Bio-sketch, November 2000

Fazli Can is a professor of Computer Science and Systems Analysis at Miami University, Oxford, OH. He has a Ph.D., 1985, in Computer Engineering from Middle East Technical University, Ankara, Turkey. He has research and teaching experience in different institutions including Arizona State University, Bilkent University, and Intel Corporation. He has published extensively on various aspects of the information retrieval problem in the journals such as ACM Transactions on Database Systems, ACM Transactions on Information Systems, Computer Journal, Information Processing Letters, Information Processing and Management, Information Systems, and Journal of the American Society for Information Science. He co-edits the ACM SIGIR Forum.