Enroll in CSE 496/896-001: Information Retrieval

Enroll in CSE 496/896-001: Information Retrieval.
Enroll in CSE 496/896-001: Information Retrieval.

CSE 496/896-001: Information Retrieval
Spring 2021, 3 credits
Instructor: Qiuming Yao
MWF 2:30-3:20 p.m.

Course Description: The objective of this class is to introduce students to the fundamentals of information retrieval concepts and technologies behind search engines in the big data era. Information retrieval as a term was first proposed by Calvin Mooers in 1950. Information retrieval is defined as the activity of obtaining information or materials which satisfies a specific information need from a large and heterogenous collection of data resources. A canonical information retrieval system is the web search engine which responds to a user's query for text-based information on a specific topic from world wide web. Although the text and document-based information retrieval is still dominant and most widely applicable in digital environments, nowadays the data objects for information retrieval can be more versatile and unstructured such as social media data, multimedia signals (i.e. images, videos, audios), biomedical records, and genomic information.

The contents of this course are composed of both fundamental concepts from lectures and advanced topics from presentations. In detail, the class will introduce foundations in basic information retrieval models, text tokenizing and indexing, query processing, retrieval ranking and filtering, machine learning based approaches, evaluation methodology, paralleled and scalable information retrieval, web crawling and searching techniques etc. This course will also arrange in-class discussions, presentations and seminars on broader, advanced and more recent topics such as multimedia based information retrieval, biomedical and genomic applications with bioinformatic approaches. Especially TREC program will be introduced to explore the real-world information retrieval research topics. In summary, this course will help students to build fundamentals from both breadth and depth of information retrieval and understand the real-world challenges behind big data search.

Recommended Text:
—Stefan Büttcher, Information Retrieval: Implementing and Evaluating Search Engines, The MIT Press; Illustrated Edition (2016)
—William Hersh, Information Retrieval: A Biomedical and Health Perspective. Springer (2020)
—Christopher D. Manning et.al., Introduction to Information Retrieval, Cambridge University Press; Illustrated edition (2008)
—Ricardo Baeza-Yates and Berthier Ribeiro-Neto, Modern Information Retrieval: The Concepts and Technology Behind Search, Addison-Wesley Professional; 2nd edition (2011)