THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2018/2019

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DRPS : Course Catalogue : School of Informatics : Informatics

Undergraduate Course: Informatics 2A - Processing Formal and Natural Languages (INFR08008)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis 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.
Course description * 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
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: ( Informatics 1 - Computation and Logic (INFR08012) AND Informatics 1 - Functional Programming (INFR08013)) OR Informatics 1 - Introduction to Computation (INFR08025)
Students MUST have passed: Informatics 1 - Data and Analysis (INFR08015) AND Informatics 1 - Object-Oriented Programming (INFR08014)
Co-requisites
Prohibited Combinations Other requirements INF1-Introduction to Computation (INFR08025) replaces INF1-Computation and Logic (INFR08012) and INF1-Functional Programming (INFR08013) from 2018/19.
Information for Visiting Students
Pre-requisitesNone
High Demand Course? Yes
Course Delivery Information
Academic year 2018/19, Available to all students (SV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 30, Seminar/Tutorial Hours 9, Supervised Practical/Workshop/Studio Hours 6, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 149 )
Assessment (Further Info) Written Exam 75 %, Coursework 25 %, Practical Exam 0 %
Additional Information (Assessment) In order to pass the course you must satisfy the following requirement:
* obtain a combined total mark of at least 40%

Assessment
Three pieces of assessed coursework, including computer-based exercises.

You should expect to spend approximately 50 hours on the coursework for this course.
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Informatics 2A - Processing Formal and Natural Languages2:00
Resit Exam Diet (August)Informatics 2A - Processing Formal and Natural Languages2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate knowledge of the relationships between languages, grammars and automata, including the Chomsky hierarchy
  2. Demonstrate understanding of regular languages, finite automata, context-free languages and pushdown automata, and how how context-free grammars may be used to model natural language
  3. Demonstrate knowledge of top-down and bottom-up parsing algorithms for context-free languages
  4. Demonstrate understanding of probabilistic finite state machines and hidden Markov models, including parameter estimation and decoding, and probabilistic context-free grammars, with associated parsing algorithms
  5. Demonstrate knowledge of issues relating to human language processing
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
Additional Information
Course URL http://course.inf.ed.ac.uk/inf2a
Graduate Attributes and Skills Not entered
KeywordsNot entered
Contacts
Course organiserDr John Longley
Tel: (0131 6)50 5140
Email: j.r.longley@ed.ac.uk
Course secretaryMs Kendal Reid
Tel: (0131 6)51 3249
Email: kr@inf.ed.ac.uk
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