Information Search and Retrieval

Information Search and Retrieval

Lecturer: Francesco Ricci

Academic year 2010-2011 - 2nd Semester

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:

Basic information retrieval concepts

Boolean retrieval

Indexing

Vector space model

Text and vector space classification

Evaluation in information retrieval

Recommender systems

Collaborative- and Content-based filtering

Hybrid recommender systems

Knowledge based recommenders

Conversational recommender systems

Evaluation of recommender systems

Human Computer Interaction and recommender systems

Context-dependent recommender systems

Decision making

Web search and link analysis

Ranking and machine learning on documents