Associating Documents to Concept Maps in Context

To be useful, automatic document classification systems must accurately place documents in categories that are meaningful to users. Because concept mapping externalizes humans’ conceptualizations of a domain, concept maps provide meaningful categories for organizing documents. Since electronic concept-mapping tools provide mechanisms for using concept maps for effective document access, using concept maps as means to classify documents provides at the same time a browsing system to access the classified documents. To enable automatically associating documents with the relevant concept maps, this paper presents a new top-down/bottom-up approach to classifying documents in the context of topically relevant concept maps. Using the target concept maps as context for extracting concepts from text, this approach generates concept-map-based indexing structures from documents and then indexes them under the concept map most compatible with the document. An experimental evaluation shows marked improvements in performance compared both to a previous bottom-up approach to this classification task and to a second baseline method using unstructured keyword-based indices.