| Extended Course Description: | Catalog Course Description:
The theoretical underpinnings of information retrieval are covered. Emphasis is given to processing of information for machine indexing and retrieval.
Pre-requisites and Co-requisites:
INFO 105 Minimum Grade: D or ISYS 105 Minimum Grade: D
and
INFO 110 Minimum Grade: D or ISYS 110 Minimum Grade: D
and
CS 260 Minimum Grade: D or CS 133 Minimum Grade: D or INFO 154 Minimum Grade: D or SE 103 Minimum Grade: D
Curriculum Role:
Much of the curriculum is based on processing highly structured information such as databases.. This course introduces the processing techniques for processing semi-structured and unstructured objects. Much of the course deals with processing text for supporting information access but other aspects text and multimedia interaction, structure, and processing are also introduced. Finally, the role and impact of information retrieval on the Web are examined.
Course Rationale:
Given how pervasive search engines are, not only for the Web, but for organizational information, students need a basic grounding in the methods of preparing text for search, matching text with queries, and displaying search results. The goal is to provide a sufficient overview of fundamental techniques used in information retrieval so that students will be able to understand new developments and specific systems with which they may have to deal.
Course Outcomes:
Upon successful completion of this course, a student will be able to:
• Identify basic theories and approaches to information retrieval and text processing.
• Understand principles of information science such as the structure and use of documents. This also includes markup languages and controlled vocabularies.
• Understand and work with the components necessary for building search engines.
• Evaluate the effectiveness of various search algorithms, interfaces, and tools.
• Understand the use and impact of search engines and related technologies on the Web. This may include topics such as natural language processing, social retrieval, and multimedia processing as well as business models for search engines.
Course Content:
Principal topics and the approximate number of weeks devoted to each are:
• Introduction to information and retrieval
• Precision & recall, and retrieval effectiveness measures
• Lexical analysis and indexing
• Data structures for storage and retrieval, Matching algorithms
• Vector, Probabilistic, and PageRank models
• Retrieval system interfaces
• Natural language processing, information extraction, and question answering
• Multimedia retrieval
• Social networking and retrieval
• Overview of current IR systems and web search engines Search engine business models.
Presentation:
Method is lecture and in-class discussion. Homework is based on the use of course-specific programs or software for the analysis and evaluation of retrieval algorithms.
Assessment:
Grade is based on homework, class participation, and examinations.
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