| CODE | LIN1121 | ||||||||
| TITLE | Language for Humans and Machines | ||||||||
| UM LEVEL | 01 - Year 1 in Modular Undergraduate Course | ||||||||
| MQF LEVEL | 5 | ||||||||
| ECTS CREDITS | 4 | ||||||||
| DEPARTMENT | Institute of Linguistics and Language Technology | ||||||||
| DESCRIPTION | This study-unit focuses on applications of Natural Language Processing, introducing students to the area through an overview of the basic concepts, terminology and methodologies used. In addition to a general introduction, the unit seeks to provide a more in-depth understanding of the area through a focus on specific core areas of NLP. The main aim of the study-unit is to introduce students to (a) the role of computing in understanding human language and facilitating tasks that involve linguistic data and/or communication; (b) the role of human language in making human-computer interaction more natural for users. The study-unit also aims to introduce basic concepts related to computing, through examples from the field of NLP. These include the concepts of (a) algorithms and data structures; (b) probability and probabilistic modelling. These concepts are introduced in an informal way, primarily through their application in specific NLP tasks. Finally, this study-unit will make students aware of NLP as an area in which linguistics has a practical application. This will be achieved through a practical component, in addition to the lecturing component. Topics for in-depth coverage will be selected from among the following: - machine translation; - automatic summarisation; - natural language generation; - question answering; - information extraction. Study-Unit Aims: The unit aims to: - familiarise students with the field of NLP and the relationship between the study of language and the study of computers; - introduce students to core NLP areas, emphasising those (such as MT and information extraction) that have become part of users' day-to-day interaction with computers; - introduce the basic concepts behind algorithms and data structures, through examples from the field of NLP. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - describe the basic concepts and use basic terminology in NLP; - identify the various areas of research that fall under NLP; - understand the links between linguistics and ICT on the basis of practical applications; - identify the areas in which NLP plays a role in everyday life. 2. Skills: By the end of the study-unit the student will be able to: - evaluate the merits of different areas of research related to NLP; - critically evaluate the role of NLP technology in communication and information processing; - analyse and compare different approaches to solving computational problems. Main Text/s and any supplementary readings: Main Texts: - Jurafsky, Daniel & Martin, James H. (2009). Speech and Language Processing. (2nd edition). Indiana: Prentice Hall. Supplementary Readings: - G. Salton and M.J McGill (1986). Introduction to Modern Information Retrieval. New York: McGraw-Hill I. Mani (2001). Automatic Summarization. Amsterdam: John Benjamins. |
||||||||
| STUDY-UNIT TYPE | Lecture and Practicum | ||||||||
| METHOD OF ASSESSMENT |
|
||||||||
| LECTURER/S | Patrizia Paggio (Co-ord.) Marc Tanti |
||||||||
|
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
|||||||||