Information Retrieval

Today more and more information is available in unstructured or poorly structured form. Examples of information of this type are textual documents, web pages, videos, photos, music, blogs, etc. The goal of this course is to enable the student to understand the foundations of managing unstructured or poorly structured information. In particular, the aim is to assist students to understand of some techniques for the indexing, retrieval, filtering, clustering, and presentation of textual and multimedia information held in digital archives and/or on the web. From this perspective the course complements what the student learned from the previous course on Data Management, where only structured information is managed. The course will be complemented by practical sessions dealing with the design, implementation, and evaluation of information retrieval systems for small and medium size collections of documents.

PREREQUISITES

• Data Management

REFERENCES

• Suggested: C. Zhai, and S. Massung. Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining. ACM Books, 2016.
• Suggested: W.B. Croft, D. Metzler, and T. Strohman. Search Engines: Information Retrieval in Practice, Pearson, 2009.