Bioinformatics and data mining

The Software Engineering group

Language technology is a hybrid field between linguistics and computer science which has many practical applications, e.g. machine translation, automatic summarization of texts, dialogue with the computer  in natural language.

The group of language technology is teaching courses on the bachelor, master as well as doctoral level (Language technology, Introduction to Computational Linguistics, Artificial Intelligence I and II, Syntax Theories and Methods, etc). Some of the courses are designed for the students of Computational Linguistics, this speciality is taught at the Faculty of Philosophy. PhD students who specialize in the field of language technology can participate in the Doctoral School of Linguistics and Language Technology one of the partners of which is the Nordic Graduate School of Language Technology.
 

The research topics of the group are: automatic morphological analysis, parsing and semantic analysis, incl. dialogue processing. The research group has conducted a joint research with linguists from the research group of computational linguistics of the University of Tartu and the Institute of the Estonian Language, and language engineers from laboratory of phonetics and speech technology of the Tallinn University of Technology and  from  Nordic countries.

Estonian morphology is modelled using finite-state transducers (two-level morphology).
The framework for automatic syntactic analysis (parsing) is based on Constraint Grammar formalism. The parser determines the syntactic functions of every word in the sentence, i. e. it performs shallow syntactic analysis. The goal of the ongoing project is to create a parser which is able to build a syntactic tree.
The research on computational semantics has been focused mainly on automatic disambiguation of word meanings. The software for semantic analysis of the sentence is in the planning stage.
The team  is studying the opportunities for dialogue modelling, in order to create software systems which are able to interact with a user in Estonian.
For the development of a machine translation system, experiments are made using statistical methods.
The group is also involved in projects of annotating

Bioinformatics and data mining work group

In different scientific fields huge amounts of data are being produced and analysed, like the data from the experiments and measurements, scientific publications, etc. Especially in molecular biology and genetics huge leaps have been taken towards generating data and novel information about DNA, RNA, and proteins and their functioning. The field of bioinformatics studies computational analysis of such data with the aim to discover new biological insights and analysis methods. The field of data mining (DM) studies the analysis methods for extremely large data sets for novel knowledge and insights. Aim of the group is to generate synergy between algorithmic research and bioinformatics research fields and to study application of data mining methodologies in bioinformatics or other application areas.

The Software Engineering group

The Software Engineering group conducts research around the following question:
How to build and maintain integrated software systems that are aligned with business operations?
The group focuses on two approaches to this general question:

• Business Process Management: Analysing and building software systems based on models capturing how an organisation works, also called business process models.
• Service-Oriented Computing: Analysing and building software systems based on the metaphor of "software as a service", usually on top of Web technology. In particular, the group conducts research aimed at Specific research topics that the group currently researches include:
• Collaborative modeling of business process modeling at different levels of details
• Managing repositories of business process models, including comparison and merging of business process models
• Measuring and improving the maintainability and interoperability of service-oriented systems
• Development of Rich Internet Interfaces that adapt to the profiles and intentions of end users