Module for PhD Students &

Postgraduates 

（English）

Web Mining Technology

Introduce the state-of-the-art and research hotspot of  Web mining technology,   discusse the methodology, algorithm and application of the three main areas,   i.e., Web structure mining, Web content mining and Web log mining, as well as   their related technologies in depth.

Specific topics include: Overview   of  Web data analysis; Web structure mining and information retrieval;   Web content mining including Machine Translation and Sentiment Analysis   Techniques and tools for evaluating the performance of Web mining algorithms;   Web anomaly pattern mining; Research on challenges and development of Web   Mining technology.

no longer deliverable

Module for PhD Students &   Postgraduates 

（English）

The basics of big data intelligent management and analysis mechanism

Big data is massive, dynamic, diversified and explosively growing information treasure, which plays a vital role in our society. 

Autumn semester,

3h per week

Key module for Undergraduate students

Principle and   Design of Databases

Experiment of   databases 

This module is a compulsory course   for computer science and technology, software engineering and information   related majors.

Topics include overview of databases,  technique development,    relational modeling, structure of database systems, relational database   theory,  database design procedure, SQL, database security, and   normalization.

An associated separete experiment course is delivered parallel,   which  focuses on database technique practical training and SQL  programming in lab.

Spring semester

3h per week + 2h lab sessions per   week

SWJTU-Leeds Joint School

Databases

(English)

Module summary:        Databases are a common component of many computer systems, storing and   retrieving data about the state of a system. This module covers the   principles of the design, architecture, implementation of database systems   and the role of database management systems. In order to understand the   design of database system an understanding of relational theory is required   as well as the tools and techniques for decomposing systems and modelling   them in an appropriate manner.This module introduces the tools for   manipulating data in databases and design principles that ensure data  security and integrity.

Objectives:       This module provides a foundation in the design and implementation of   databases with an emphases on relational database systems.

Learning outcomes:        On successful completion of this module a student will have demonstrated the   ability to: - describe the purpose and architecture of database management   systems. - use appropriate tools to manipulate database systems. - design and   implement a database using appropriate tools. - apply relational modelling   techniques to real world situations. - apply normalisation and explain the   advantages and disadvantages of normalisation. - describe the ethical, legal   and security related issues concerning the implementation and administration   of databases and their management systems.

Spring semester

3h/week, 10 weeks

SWJTU-Leeds Joint School

Data Mining 

by Eric Atwell, Yan   Zhu

Module summary:      This   module explores the knowledge discovery process and its application in   different domains such as text and web mining. You will learn the principles   of data mining; compare a range of different techniques and algorithms and   learn how to evaluate their performance.

Objectives:     On   completion of this module, students should be able to: -Identify all of the   data, information, and knowledge elements, for a computational science   application. -understand the components of the knowledge discovery process   -understand and use algorithms, resources and techniques for implementing   data mining systems; -understand techniques for evaluating different   methodologies -demonstrate familiarity with some of the main application   areas; -demonstrate familiarity with data mining and text analytics tools.

Learning outcomes:      On   completion of the year/program students should have provided evidence of   being able to: -demonstrate a broad understanding of the concepts,   information, practical competencies and techniques which are standard   features in a range of aspects of the discipline; -apply generic and subject   specific intellectual qualities to standard situations outside the context in   which they were originally studied; -appreciate and employ the main methods   of enquiry in the subject and critically evaluate the appropriateness of   different methods of enquiry; -use a range of techniques to initiate and   undertake the analysis of data and information; -adjust to professional and   disciplinary boundaries; -effectively communicate information, arguments and   analysis in a variety of forms.

Spring semester

2h/week, 12 weeks