Automatic construction of networks of concepts characterizing document databases

We report results of a study that involved the creation of knowledge bases of concepts from large, operational textual databases. Two East-bloc computing knowledge bases, both based on a semantic network structure, were created automatically using two statistical algorithms. With the help of four East-bloc computing experts, we evaluated the two knowledge bases in detail in a concept-association experiment based on recall and recognition tests. In our experiment, one of the knowledge bases that exhibited the asymmetric link property out-performed all four experts in recalling relevant concepts in East-bloc computing. The knowledge base, which contained about 20,000 concepts (nodes) and 280,000 weighted relationships (links), was incorporated as a thesaurus-like component into an intelligent retrieval system. The system allowed users to perform semantics-based information management and information retrieval via interactive, conceptual relevance feedback.