Undergraduate Course: Informatics 2A - Processing Formal and Natural Languages (INFR08008)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Credits | 20 |
| Home subject area | Informatics |
Other subject area | None |
| Course website |
http://course.inf.ed.ac.uk/inf2a |
Taught in Gaelic? | No |
| Course description | This course is about processing natural and artificial languages, building on material covered in Informatics 1 concerning finite state machines and regular expressions. This course will consider how the same models of language can be used to describe and analyse both formal languages (such as programming languages) and natural languages (text and speech). It will include material on formal languages and grammars, probabilistic grammars (including hidden Markov models), semantic analysis and human language processing. Examples will be drawn from computer languages and natural language. |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
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| Delivery period: 2013/14 Semester 1, Available to all students (SV1)
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Learn enabled: Yes |
Quota: None |
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Web Timetable |
Web Timetable |
| Course Start Date |
16/09/2013 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 30,
Seminar/Tutorial Hours 9,
Supervised Practical/Workshop/Studio Hours 18,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
137 )
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| Additional Notes |
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| Breakdown of Assessment Methods (Further Info) |
Written Exam
75 %,
Coursework
25 %,
Practical Exam
0 %
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| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | Informatics 2A - Processing Formal and Natural Languages | 2:00 | | | Resit Exam Diet (August) | | 2:00 | |
Summary of Intended Learning Outcomes
1 - Demonstrate knowledge of the relationships between languages, grammars and automata, including the Chomsky hierarchy;
2 - Demonstrate understanding of regular languages and finite automata;
3 - Demonstrate understanding of context-free languages and pushdown automata, and how how context-free grammars may be used to model natural language;
4 - Demonstrate knowledge of top-down and bottom-up parsing algorithms for context-free languages;
5 - Demonstrate understanding of probabilistic finite state machines and hidden Markov models, including parameter estimation and decoding;
6 - Demonstrate awareness of probabilistic context-free grammars, and associated parsing algorithms;
7 - Demonstrate knowledge of issues relating to human language processing. |
Assessment Information
Written Examination 75
Assessed Assignments 25
Oral Presentations 0
In order to pass the course you must satisfy all of the following requirements:
* achieve at least 35% in the examination;
* achieve a total of at least 25% in assessed coursework;
* obtain a combined total mark of at least 40%
Assessment
Three pieces of assessed coursework, including computer-based exercises.
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Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
* Grammars and the Chomsky Hierarchy
* Regular languages, Finite state automata (FSA), probabilistic FSAs
* Context-free languages and Push-down automata
* Ambiguity and solutions to the problem
* Deterministic parsers
* Chart parsers
* Probabilistic context-free grammars
* Modelling semantics
* Context-sensitive languages
* Turing machines and computability
* Models of human language processing
* Overview of language technology
Relevant QAA Computing Curriculum Sections: Natural Language Computing; Theoretical Computing; Compilers and Syntax Directed Tools |
| Transferable skills |
Not entered |
| Reading list |
* Dexter Kozen. Automata and Computability. Springer-Verlag, 2000.
* Dan Jurafsky and James Martin. Speech and Language Processing (*2nd* Edition). Prentice-Hall, 2008.
Natural Language Processing with Python, Bird, Klein & Loper, O'Reilly Publishers 2009
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| Study Abroad |
Not entered |
| Study Pattern |
Lectures 30
Tutorials 9
Timetabled Laboratories 18
Non-timetabled assessed assignments 50
Private Study/Other 93
Total 200 |
| Keywords | Not entered |
Contacts
| Course organiser | Prof Colin Stirling
Tel: (0131 6)50 5186
Email: cps@inf.ed.ac.uk |
Course secretary | Ms Kendal Reid
Tel: (0131 6)50 5194
Email: kr@inf.ed.ac.uk |
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© Copyright 2013 The University of Edinburgh - 13 January 2014 4:26 am
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