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The literature for this Course Syllabus has not yet been finalised.

Mälardalen University, School of Education, Culture and Communication

Objectives

The course aims to provide students with knowledge of key mathematical ideas, concepts, methods, algorithms and computational tools behind the success of the Internet and Internet-based technologies, and to explain the basic mathematical concepts and techniques with concrete examples of applications in modern information and Internet technologies and other technology and society. The course will also provide training in logical and algorithmic thinking, and in mathematical modeling and computational techniques of particular importance for applications in the Internet and information technology, as well as the ability for independent analysis of mathematical problems and models used in Internet and database technologies.

Learning objectives

After completing the course, students should be able
- Explain basic mathematical concepts and principles that form the foundation of the Internet as a large growing network structure consisting of linked information resources
- Describe the basic mathematical principles and structures of contemporary search engines and search technology on the Internet and in databases
- Explain basic mathematical principles behind the algorithms for effective relevance ranking of information and results, including algorithms and its modifications, which are used by leading modern search engines
- Briefly explain the main mathematical structures, problems and algorithms related to the modeling of communication within social media and their impact on public opinion and decision-making processes within the business, financial markets and public institutions at national and international level
- Explain the basics for some distance-based, statistical and other mathematical methods and problems used in text mining and NLP ("Natural language processing") and describe examples of applications of these in different sectors of technology and society
- Briefly explain such mathematical concepts from matrix analysis, discrete mathematics, graph theory, stochastic processes, Markov chains, and mathematical statistics that are central to data mining in Internet and databases

Course content

- Graphs, matrices and distance mathematical foundation for the internet, databases and other information resources, and for mathematical search engine optimization
- Optimization and ranking in linked data structures
- Eigenvalues and eigenvectors of large matrices with special structural features and their central importance to searching, ranking and optimization algorithms for internet and large databases
- Google's PageRank algorithm and its modifications. Matrix iterations and matrix factorizations of numerical algorithms for the calculation of eigenvectors and eigenvalues and page rank
- Introduction to Markov chains as an alternative model for page rank and search on the internet and in other linked data structures.
- Distance, graphs and statistical techniques in text mining, NLP ("Natural Language Processing"), relevance ranking and comparison of texts.
- Graphs and matrices in models for communication and dissemination of information in social media like Facebook, Twitter and LinkedIn as well as for the relevance ranking of information as a tool to influence public opinion and decision making.

Teaching methods

Lectures and tutorials to work individually and in groups.

Prerequisites

120 credits from one/some of these subjects/disciplines: engineering, science, business administration or economics including Discrete Mathematics 7.5 credits and Basic vector algebra 7.5 hp.

Examination

Rules and regulations for examinations in undergraduate education at Mälardalen University

Marks

3, 4 or 5.

Workload

1.5 credits correspond to approximately 40 hours per week. The individual labor input, i.e. hours per week, may however vary depending on previous knowledge or other circumstances.

Literature

The literature can be found in the university's digital archive.