Computer Science

The course introduces theories and techniques of natural language processing and language technology. It covers the whole field, from speech recognition and synthesis to semantics and dialogue. The course focuses on industrial and laboratory applications, such as document retrieval on the Internet, information extraction, conversational agents, and verbal interaction in virtual worlds. Fundamental algorithms are described using Prolog or regular expressions. Topics covered in this course include an overview of language processing (applications, disciplines of linguistics, examples); Corpus and word processing (regular expressions, automata, an introduction to Perl, concordances, tokenization, counting words, collocations); morphology, transducers, and part-of-speech tagging; Prolog to write phrase-structure grammars (constituents, trees, using Prolog to do natural language analysis, DCG rules, variables, getting the syntactic structure, compositional analysis to get the semantic structure); syntactic formalisms (constituency and dependency, chart parsing, statistical parsing, functions, dependency parsing); semantics (formal semantics, lambda-calculus, compositionality such as nouns, verbs, determiners, words and meaning, lexical semantics, case grammars, semantic grammars); discourse and dialogue (rhetoric, anaphora, structure, RST, automata, pairs, speech acts, multimodality); and an overview of speech synthesis and speech recognition.

The goal of this course is to introduce the operation of computer systems at the level of Instruction Set Architectures (ISA). It provides a basic understanding of the design principles that govern modern computer architectures and their components. Special attention is paid to (super scalar) pipelining and memory hierarchy techniques including caches. Implementation and efficiency issues are exemplified. Metrical performance analysis methods are discussed to evaluate architectural alternatives. The course introduces the foundations of low-level computer functioning. The main topics include computer systems, low-level programming techniques, the techniques of RISC processors and pipelining, cache memory, and virtual memory. The course also illuminates the alternative design principles of modern computer architectures in order to provide an understanding of their impact on performance. Quantitative methods to evaluate design principles for performance constitute an important subject of the course.

This course offers a study of databases. Topics include: information systems, databases, and database management systems; modeling methodologies; management of semi-structured and complex data, distributed and noSQL databases; relational databases; design of a database-- relational model; query languages-- SQL language; noSQL databases; comparison of relational databases to new noSQL stores; noSQL database types, installation, use, and deployment.

This course addresses the effective use of cloud technology in digital cultural and creative projects including: versatile digital publishing, website design, web community development, digital imaging, animation, video and media production management. As a specific objective, we emphasize to cap off a team project more than an individual task. This course takes account of the inter-discipline of humanities and information technology through media application. The learning method focuses on problem solving oriented approach. The learning activity designates a hands-on assignment and requires a complete output in the form of publishable presentation.

This course examines the method and process of problem analysis and mathematical model establishment; the algorithm design strategy and its key points--recursion, brute force, divide and conquer, greed, dynamic programming, backtracking and branch and bound, random, approximation, etc.; and the expression of algorithm complexity and the basic method of complexity analysis.