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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014
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DRPS : Course Catalogue : School of Informatics : Informatics

Undergraduate Course: Text Technologies (Level 10) (INFR10025)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) Credits10
Home subject areaInformatics Other subject areaNone
Course website http://www.inf.ed.ac.uk/teaching/courses/tts Taught in Gaelic?No
Course descriptionThe 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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Informatics 2A - Processing Formal and Natural Languages (INFR08008)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Text Technologies (Level 11) (INFR11027)
Other requirements Successful completion of Year 3 of an Informatics Single or Combined Honours Degree, or equivalent by 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]
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Not being delivered
Summary of Intended Learning Outcomes
1 - Describe the main algorithms for processing, storing and retrieving text.
2 - Show familiarity with theoretical aspects of IR, including the major retrieval models.
3 - Discuss the range of issues involved in building a real search engine
4 - Evaluate the effectiveness of a retrieval algorithm
Assessment Information
Written Examination 70
Assessed Assignments 30
Oral Presentations 0

Assessment
There will be a final exam, contributing 70% of the course mark. The remaining 30% will be assessed through a combination of problem sets and programming exercises involving application of existing algorithms and evalution techniques.

If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
Special Arrangements
None
Additional Information
Academic description Not entered
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
Transferable skills Not entered
Reading list Search Engines: Information Retrieval in Practiceż, W.B. Croft, D. Metzler, T. Strohman, Addison Wesley, 2008
Study Abroad Not entered
Study Pattern Lectures 20
Tutorials 0
Timetabled Laboratories 0
Non-timetabled assessed assignments 24
Private Study/Other 56
Total 100
KeywordsNot entered
Contacts
Course organiserDr Mary Cryan
Tel: (0131 6)50 5153
Email: mcryan@inf.ed.ac.uk
Course secretaryMiss Kate Farrow
Tel: (0131 6)50 2706
Email: Kate.Farrow@ed.ac.uk
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