Designing User-Interface for a Digital Library with Concept Learner Assisting Users to Find the Required Documents

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The vocabulary problem in information retrieval can be dissolved and the document/query contents can be well captured when the document/query terms are replaced by their senses in a concept hierarchy. The point is how to specify the appropriate senses. We first formulate methods of treating term-sense ambiguities, which select only the senses that contribute to keep the retrieval performance high and express the documents contents concisely, by capturing conceptual relations between a query and a document through m-to-l correspondences of the senses.The concept hierarchies in the above are edited so as to reflect the conceptual relations common to all the users, and therefore they will not reflect the individual way of thinking. We secondly proposed an information retrieval paradigm, where the documents to be examined are collected in a form of a digital library and a user is assisted when he/she browses in a digital library to retrieve the documents meeting his/her requirements. The assistance information is caught by an instance-based learning algorithm, which collects interactively the relevant/non-relevant documents.The advantages of the proposed methods are fully tested by computational and statistical experiments on two test-collections as to computer/information science and medical science. A digital library and its navigator are also designed and constructed so that the user's perceptual burden for browsing is minimized.