Course Descriptor

Course:   Text Technologies (Level 11)

Course Web page

Credit Points	10
Credit Level	11
Acronym	INF-5-TTS
Study Pattern	Study Format		Hours
	Lectures		20
	Tutorials		0
	Timetabled Laboratories		0
	Non-timetabled assessed assignments		24
	Private Study/Other		56
	Total		100

Pre-requisite Courses
Other Pre-requisite Requirements	For Informatics PG and final year MInf students only, or by special permission of the School. This course has the following mathematics prerequisites: 1. Probability theory: random variables, expectation, joint and conditional probabilities; discrete and continuous univariate distributions. [at the level of MI1 and MI4] 2. Algebra: definition of vectors and matrices; vector addition and inner product; matrix multiplication. [at the level of MI2] 3. Calculus: functions of several variables, univariate integrals and derivatives, univariate maxima and minima. [at the level of MI1] 4. Special functions: log, exp [at the level of MI1]
Co-requisites/Forbidden Combinations	Text Technologies (Level 10) forbidden

Short Description

The course deals with retrieval technologies behind search engines, such as Google. The course will aim to strike a balance between theoretical and system-related aspects of the field. The course will cover:

1. Theoretical aspects, including properties of text, queries, relevance, major retrieval models and evaluation;
2. System-related aspects, including crawlers, text processing, index construction and retrieval algorithms; and
3. Applications, including cross-language and multi-media search.

The same material will be covered in the level 10 and level 11 versions of the course. Level 11 students should expect more challenging assignments and an increased programming load.

Summary of Intended Learning Outcomes

Assessment

Syllabus

Lectures will cover the following topics, with a typical lecture integrating material from more than one aspect.

1. Theoretical aspects:
   • The nature of text, Zipf and Heaps laws, clumping
   • Information needs, queries and relevance
   • Evaluation of retrieval systems
   • Vector-space model and latent semantic indexing
   • Probabilistic model and relevance feedback
   • Language-modeling approaches
   • Inference networks and structured queries
2. Systems aspects:
   • Search engine architecture
   • Crawling and feeds
   • Text processing and representation
   • Indexing methods and compression
   • Distributed search and meta-search
   • Presentation and visualization of search results
3. Applications:
   • Web search
   • Cross-language retrieval
   • Multi-media retrieval
   • Clustering and classification
   • Topic detection and tracking
   • Passage retrieval and question-answering

Relevant QAA Computing Curriculum Sections:  Information Retrieval, Natural Language Computing, Human-Computer Interaction (HCI), Developing Technologies

Reading List

• “Search Engines: Information Retrieval in Practice”, W.B. Croft, D. Metzler, T. Strohman, Addison Wesley, 2008. Primary text, photocopies will be provided by instructor.
• “Introduction to Information Retrieval”, C.D. Manning, P. Raghavan and H. Schutze, Cambridge University Press, 2008.
• “Managing Gigabytes”, I.H. Witten, A. Moffat, T.C. Bell, Morgan Kaufmann, 1999.
• “Information Retrieval”, C. J. van Rijsbergen, Butterworths, 1979.
• “Recommended Reading for IR Research Students”, A. Moffat, J. Zobel, D. Hawking. SIGIR Forum, 39(2), 2005.

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