CS499/699 Introduction to Information Retrieval

Instructor: T. K. Prasad
Phone No.: (937)-775-5109
Email: t.k.prasad@wright.edu
Home Page: http://www.cs.wright.edu/~tkprasad

Quarter: Summer, 2008.
Class Hrs: TuTh 6:05pm-7:20pm.
Office Hrs: 3-4pm. 395 Joshi Research Center (or by appointment)

Course Objective

To cover the foundations of information retrieval, to enable design, analysis and implementation of IR systems.

Course Prerequisite

CS600 Data Structures and Algorithms

Course Description

This course covers models for information retrieval, techniques for indexing and searching, algorithms for classification and clustering, latent semantic indexing, link analysis and ranking.

Course Load

The course load includes a programming project, a presentation, a midterm exam and a final exam.

Required Texts

"Introduction to Information Retrieval". C.D. Manning, P. Raghavan, H. Schütze. Cambridge University Press, 2009.

Recommended Texts

"Modern Information Retrieval". Ricardo Baeza-Yates (Author), Berthier Ribeiro-Neto. Addison Wesley, 1999.
"Mining the Web: Discovering Knowledge from Hypertext Data". Soumen Chakrabarti. Morgan Kaufmann, 2003.
"Information Retrieval: Algorithms and Heuristics", D. Grossman and O. Frieder. Springer, 2nd Ed., 2004.
"Managing Gigabytes: Compressing and Indexing Documents and Images", I. Witten, A. Moffat, and T. Bell. 2nd Ed., Morgan Kaufmann, 1999.
"Understanding Search Engines: Mathematical Modeling and Text Retrieval", Michael W. Berry, and Murray Browne, 2nd Ed., SIAM, 2005.

Reference URLs

Lucene Text Search Engine (http://lucene.apache.org/)
Singular Value Decomposition (http://www.uwlax.edu/faculty/will/svd/index.html)
Information Retrieval and Web Mining (http://www.stanford.edu/class/cs276/cs276-2006-syllabus.html)
Strang's Linear Algebra Course (MIT) (http://ocw.mit.edu/OcwWeb/Mathematics/18-06Spring-2005/CourseHome/index.htm)

Grading

The A/B/C/D/F letter grade will be assigned at the end of the course.

Tentative Class Schedule and Syllabus

	Topics	Addl. Reading
Class 1	Information Retrieval; The Boolean Model	MIR-1
Class 2	The Vector Space Model : Term Weighting and Scoring	MIR-2 (IIR-6)
Class 3	Inverted Index Construction	IIR-1 (MIR-8.2)
Class 4	Dictionary and Postings; Query Processing	IIR-2 (MIR-7.2)
Class 5	Tolerant Retrieval	IIR-3
Class 6	Index Construction	IIR-4 (MG-5)
Class 7	Index Compression	IIR-5 (MG 3.3-4)
Class 8	Evaluation in Information Retrieval	MIR-3 (IIR-8)
Class 9	Midterm Exam (July ##)
Class 10	Relevance Feedback and Query Expansion	IIR-9 (MIR-5.2-4)
Class 11	Vector Space Classification	IIR-14
Class 12	Flat Clustering	IIR-16
Class 13	Hierarchical Clustering	IIR-17
Class 14	Web Characteristics	IIR-19
Class 15	(cont'd)
Class 16	Web Search: Crawling and Indexes	IIR-20
Class 17	Link Analysis	IIR-21
Class 18	Support Vector Machines	IIR-15
Class 19	Linear Algebra: Matrix Decompositions	SVD-URL
Class 20	Latent Semantic Indexing	IIR-18
	Final Exam (August ##)

T. K. Prasad ( 08 Jan 2008 )