Information Search and Retrieval Search
Lecturer: Francesco Ricci

Academic year 2014-2015 - 2nd Semester


Objectives | Syllabus | Exam | Reading Material | Handouts and Assignments 

Start date:  Thursday, February 26th 10:30-12:30, Room E411
Lectures: Tuesday  10:30-12:30, Thursday 10:30-12:30
Labs: Tuesday 14:00-16:00
Hours of availability for students and tutoring: Tue: 16:00-18:00, by prior arrangement via e-mail.

Objectives: 

The first objective of this course is to present the scientific underpinnings of the field of Information Search and Retrieval. We will be concerned with basic information retrieval concepts and more advanced techniques for information filtering and decision support. 

The World Wide Web has become the primary source of information for leisure and work activities and its huge content would be wasted if that information could not be found, analyzed, and exploited so that each user can quickly find information that is both relevant and comprehensive for their needs. Moreover the Web has become a principal driver of innovation and a range of new techniques have been introduced to tame and exploit its information content. Personalization and information filtering techniques, e.g., Recommender systems, are now largely used, particularly in eCommerce web sites, for easing the information search and discovery processes, and increasing customer fidelity and conversion rates.

Hence, the second objective of this course is to provide to the student a rich and comprehensive catalogue of information search tools that can be exploited in the design and implementation of a specific Web site, such an eCommerce or eGovernment applications for travel and tourism or health.

Syllabus:

Exam
Reading Material

The suggested book for the information retrieval topics is:
There is a new book dedicated to recommender systems that you may want to use:
There is also a good collection of papers on personalized and adaptive and some of these papers will be suggested as reading material:
All the required reading material will be provided during the course and will be available in electronic format. Copy of the slides will be available as well.

Lectures

Part 1   -  Introduction to Information Retrieval and Recommender Systems - part1.pdf Part 2 - Boolean Retrieval - part2.pdf Part 3 -  Dictionaries and tolerant retrieval - part3.pdf
Part 4 -  Index Construction - part4.pdf
Part 5 - Scoring, Term Weighting and the Vector Space Model - part5.pdf Part 6 - Scoring in a Complete Search System - part6.pdf
Part 7 - Evaluation of  Information Retrieval Systems - part7.pdf
Part 8 - Relevance feedback - part8.pdf
Part 9 - Text classification and Naive Bayes - part9.pdf
Part 10 - Vector space classification - part10.pdf
Part 11: Collaborative Filtering - part11.pdf
Part 12: Advanced Topics in Collaborative Filtering - part12.pdf
Part 13: Item-to-Item Filtering and Matrix Factorization - part13.pdf
Part 14: Content-Based Filtering and Hybrid Systems - part14.pdf
Part 15: Context-Dependent Information Filtering - part15.pdf
Part 16: Recommendations for groups  - part16.pdf