A Visual Enhancement for Metadata Generation Tools: A Semi-Automatic Approach via KWIC and Highlighting

This paper reports on a study that examined a visual enhancement for NC Health Info, an online health information portal for NC residents. The research goal was to improve the Health Topic assignment with a semi-automatic approach via KWIC and highlighting. The study had three components: a contextual inquiry investigating improvable areas; a prototype developed according to the contextual inquiry findings; and a comparative user study evaluating the effects of the proposed approach on the assignment of Health Topics and users' perceptions of two systems. The experiment results proved that the prototype significantly reduced the cataloging time and may potentially improve metadata quality. Additionally, measured users' perceptions of the proposed system were positive. This approach is expected not only to improve NC Health Info services but further enhance metadata generation tools in the future

BayesTH-MCRDR algorithm for automatic classification of web document

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