Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Knowledge Processes and Ontologies
IEEE Intelligent Systems
GETESS: Constructing a Linguistic Search Index for an Internet Search Engine
NLDB '00 Proceedings of the 5th International Conference on Applications of Natural Language to Information Systems-Revised Papers
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Knowledge Management Systems (KMSs) are of increasing interest in economy to collect, store and re-use company-relevant knowledge as a resource to gain productivity. In this paper we demonstrate how to leverage structured information for its efficient re-use. We propose the development of ontologies to represent the knowledge to be stored. As it is any how the case that in a KMS knowledge has to be fostered the step towards a systematic structuring is a solution which suggests itself. In the paper we outline our experience with the development of an ontological model of the KMS of the IT company sd&m (called K-WEB) in view of a restructuring process of the whole system. On the basis of the implemented ontology we illustrate how frequently asked questions in the company which are difficult to be answered by the currently deployed full-text retrieval-system (for instance, experienced colleagues in a specific programming language can only be found if the currently considered list of relevant documents can be classified as the employee's home page due to the fact that only on this page a pointer into the skills hierarchy is provided in the K-WEB whereas a full text retrieval system can neither regard the document type nor the physical pointer) become simple in a structural representation.