Automatic generation of hypertext knowledge bases

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Abstract
A model of knowledge-based text condensation is presented which has been implemented as part of the text analysis system TOPIC. The condensation process transforms the text representation structures resulting from the text parse into a more abstract thematic description of what the text is about, filtering out irrelevant knowledge structures and preserving only the most salient concepts. The topical structure of a text, finally, is represented in a hierarchical text graph which supports variable degrees of abstraction for text summarization as well as content-oriented retrieval of text knowledge. Due to their non-linear organization, text graphs share a lot of similarities with hypertexts. Their contribution to this field incorporates a methodology for the automatic generation of hypertexts from given full-text files, a close coupling of basic hypertext notions (links, nodes) to the formal specifications of a frame representation model, and conceptual navigation and filtering facilities which allow a user-defined level of information granularity when accessing hypertext knowledge bases.

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