An automatic mark-up approach for structured document retrieval in engineering design
Information and knowledge retrieval has been recognized as a key issue in engineering design. A great deal of design-related information used and generated within engineering companies is formally recorded in documents. These documents become more useful if they are structured in a consistent way so...
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Veröffentlicht in: | International journal of advanced manufacturing technology 2008-08, Vol.38 (3-4), p.418-425 |
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Sprache: | eng |
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Zusammenfassung: | Information and knowledge retrieval has been recognized as a key issue in engineering design. A great deal of design-related information used and generated within engineering companies is formally recorded in documents. These documents become more useful if they are structured in a consistent way so that they can be retrieved and their contents accessed more effectively. Achieving useful structure in electronic documents relies on embedding some sort of mark-up or coding that is computer-understandable. Manual mark-up is time-consuming and costly. This paper proposes a knowledge engineering approach to automatic document mark-up employing XML (the eXtensible Mark-up Language) to ’tag’ explicitly the structural information. The focus here is on long and complex engineering documents. A three-level model is explored to achieve automatic semantic mark-up using a set of document decomposition schemes. The model includes a strategic level which identifies document typographical features based on such things as styles, inference or templates; a tactical level to define the rules to realize semantic mark-up according to the document features; and an operational level to perform the computational implementation of the mark-up rules. By making document structure explicit, information retrieval can be made more focused by returning not just whole documents but the
document components
that are most relevant or of most interest to the engineering designer, and information relevant to the designer’s need both with respect to document
structure
and
content
, not
content
alone. In addition, interpretation of useful structure by the human user can be hardwired into documents, which allows us to move closer to true semantic level retrieval. |
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ISSN: | 0268-3768 1433-3015 |
DOI: | 10.1007/s00170-007-1342-z |