Computational linguistics can be viewed in two ways. On one hand, it is the application of various techniques and results from computer science to linguistics, in order to investigate such fundamental problems as what people know when they know a natural language, what they do when they use this knowledge, and how they acquire this knowledge in the first place. On the other, it is the application of various techniques and results from linguistics to computer science, in order to provide such novel products as computers that can understand everyday human speech, translate between different human languages, and otherwise interact linguistically with people in ways that suit people rather than computers. Knowledge representation can likewise be viewed in two ways. On one hand, it attempts to construct mathematical representations of what knowledge is, how it is used, and how it is modified. On the other, it exploits these representations in order to equip computers with simulated intelligence.
Though knowledge representation and computational linguistics clearly address broadly similar research problems, research within each of these fields has hitherto been largely ignorant of research within the other. This ignorance is doubly unfortunate, since interdisciplinary research in knowledge representation and computational linguistics would be likely to yield important scientific advances in the representation, use and acquisition of linguistic knowledge, advances with obvious potential for industrial application in products as diverse as message understanding software, automatic language acquisition devices, user-friendly network navigators, intelligent information retrievers, and machine-aided translation tools. However, the ignorance the two fields have of each other both fosters and is fostered by a wide gulf between the educations received by students of knowledge representation and students of computational linguistics. Attempts to break this vicious circle began in the mid 1980's with the founding of several institutionalised interdisciplinary programmes of education that included computational linguistics and knowledge representation. However, the enormous political and economic changes that occurred at the end of the 1980's meant that such programmes were extremely rare in CEE.
The CLaRK programme provides a two-site international centre of excellence in computational linguistics and knowledge representation that offers graduate students from CEE the opportunity to pursue their research and education within the broad computational, linguistic, mathematical and philosophical framework necessary nowadays for advanced research in computational linguistics and knowledge representation. The students follow an `apprenticeship' education model by pursuing their individual researches within a collaborative project-based research environment. More exactly, the programme initiates a small number of research projects in computational linguistics and knowledge representation. Graduate students then conduct their individual researches while participating in CLaRK research projects closely related to their thesis topics. Practical experience at the host institutions of the programme shows that such a combination of individual and collaborative research reduces the sense of isolation typically felt by graduate students working alone, encourages the early presentation of work at conferences and in journals, and provides group-based research experience that is invaluable when students subsequently look for employment. In addition, the program will produce high-quality teaching materials to be aired and tested at annual CLaRK summer schools, the first in Germany and the second in Bulgaria. The working language of the programme is English.
If you want to know more, here is a more detailed (and much longer) description of the programme.
Frank Richter (fr@sfs.uni-tuebingen.de)