Burghard B. Rieger:
In: Raubold, E. (ed.): Innovative Developments and Applications of Microelectronics and Information Technology (Proceedings 2nd German-Chinese Electronics Week (GCEW-91), Shanghai, VR China) Berlin/Offenbach (VDE-Verlag) 1991, pp.193-200
From the linguistic viewpoint natural language texts,
whether stored electronically or written conventionally, will in
the foreseeable future provide the major source of scientifically,
historically, and socially relevant information. Due to the new
technologies, the amount of such textual information continues to
grow beyond manageable quantities. Availability of data,
therefore, no longer serves to solve an assumed problem of lack of
information to fill a knowledge gap in a given
instance, but will instead create a new problem which arises from
the abundance of information that confronts the potential user.
There is an increasing need to employ computers more effectively than hitherto for the analysis of natural language material. Although the demand is high for intelligent machinery to assist in or even provide speedy and reliable selection of relevant information under individual aspects of interest from any subject domain, such systems are not yet available. Development of earlier proposals [2], have resulted in some advances [3] towards an artificial meaning learning and understanding system (MLU) as core of a cognitive information processing system (CIPS) which will be capable of learning to understand (i.e. identify and interpret) the meanings implied in natural language texts by generating perspectival and dynamic conceptual dependencies (i.e. semantic inferencing) [4]. In view of a text skimming system under development [5], a basic cognitive algorithm has been designed which detects from the textual environment the system is exposed to those structural information which the system is able to collect due to its own two-level knowledge structuredness. It allows for the automatic generation of a pre-predicative and formal representation of conceptual knowledge which the system will both, gather from and modify according to the input texts processed. The system's internal knowledge representation is planned to be made accessible in a dialog interface. This will allow users to make the system skim masses of texts for them, display its acquired knowledge in dynamic structures of conceptual dependencies, provide valuable clues for relevant connections, and help to avoid unnecessary reading of irrelevant texts.
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