Postgraduate Course: Text Technologies (Level 11) (INFR11027)
|School||School of Informatics
||College||College of Science and Engineering
||Availability||Not available to visiting students
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
|Home subject area||Informatics
||Other subject area||None
||Taught in Gaelic?||No
|Course 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.
Entry Requirements (not applicable to Visiting Students)
|Prohibited Combinations|| Students MUST NOT also be taking
Text Technologies (Level 10) (INFR10025)
||Other 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]
|Additional Costs|| None
Course Delivery Information
|Delivery period: 2011/12 Semester 1, Not available to visiting students (SS1)
||WebCT enabled: No
|No Classes have been defined for this Course|
||Week 1, Monday, 12:10 - 13:00, Zone: Central. Old College Lt183 |
|Main Exam Diet S2 (April/May)||2:00|
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
|Written Examination 70|
Assessed Assignments 30
Oral Presentations 0
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. Compared to the level 10 version of this course, level 11 students will undertake more challenging assignments and an increased programming load.
||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
* 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
||* &«Search Engines: Information Retrieval in Practice&ª, W.B. Croft, D. Metzler, T. Strohman, Addison Wesley, 2008. Primary text, photocopies will be provided by instructor.
* &«Introduction to Information Retrieval&ª, C.D. Manning, P. Raghavan and H. Schutze, Cambridge University Press, 2008.
* &«Managing Gigabytes&ª, I.H. Witten, A. Moffat, T.C. Bell, Morgan Kaufmann, 1999.
* &«Information Retrieval&ª, C. J. van Rijsbergen, Butterworths, 1979.
* &«Recommended Reading for IR Research Students&ª, A. Moffat, J. Zobel, D. Hawking. SIGIR Forum, 39(2), 2005.
Timetabled Laboratories 0
Non-timetabled assessed assignments 24
Private Study/Other 56
|Course organiser||Dr Michael Rovatsos
Tel: (0131 6)51 3263
|Course secretary||Miss Kate Weston
Tel: (0131 6)50 2701
© Copyright 2011 The University of Edinburgh - 16 January 2012 6:17 am