Text Analytics (CE807)
Module Supervisor: Shoaib Jameel
The aim of this module is to provide students with an understanding of text analytics and its applications. Students will be introduced to the state of the art methods for extracting structured information (e.g. opinions about products) from unstructured textual data, in particular in social media; and to techniques for summarizing and analyzing this information.
More details on this module can be found here.
Information Retrieval (CE706)
Module Supervisor: Alba Garcia
Search engines have become the first entry point into a world of knowledge and they form an essential part of many modern computer applications. While much of the underlying principles have been developed over decades, the landscape in search engine technology has changed dramatically in recent years to deal with data sources magnitudes larger than ever before (the rise of “big data”). As a result of that new paradigms for storing, indexing and accessing information have emerged. This module will provide the essential foundations of information retrieval and equip the students with solid, applicable knowledge of state-of-the-art search technology.
More details related to the module can be found here.
Natural Language Engineering (CE887)
Module Supervisor: Yunfei Long
This course provides a strong foundation to understand the fundamental problems in NLE and also equips students with the practical skills to build small-scale NLE systems. Students are introduced to three core ideas of NLE: a) gaining an understanding the core elements of language— the structure and grammar of words, sentences and full documents, and how NLE problems are related to defining and learning such structures, b) identify the computational complexity that naturally exists in language tasks and the unique problems that humans easily solve but are incredibly hard for computers to do, and c) gain expertise in developing intelligent computing techniques which can overcome these challenges.
The aim of this module is to introduce key ideas and techniques used in the design and implementation of natural language engineering applications. We will primarily cover statistical methods and will look at the use of such methods in applications.