Abstract
Management of textual documents obtained from various online sources represents a challenge in emerging e-commerce environments, where individuals and organisations have to perform continual surveillance of important events or trends pertinent to multiple topic areas of interest. Observations of textual document management by individuals and organisations have suggested the popularity of using categories to organise, archive and access documents. The sheer volume and availability of documents obtained from the internet make manual document-category management prohibitively tedious, if practicable or effective at all. An automated approach underpinned by appropriate artificial intelligence techniques has potential for solving this problem. In this vein, a critical challenge is the preservation of the user's perspective on semantic coherence in different documents and thus supports his or her preferred practice for document groupings. Motivated by the significance of, and the need for automated document-category management, the current research proposed and experimentally examined an evolution-based approach for supporting user-centric document-category management in e-commerce environments. Specifically, we designed and implemented the Category Evolution (CE) technique, capable of supporting personalised document-category management by taking into account categories previously established by the user. Our evaluation results suggest that CE exhibited satisfactory effectiveness and reasonable robustness in different scenarios and achieved a performance level better than that recorded by the benchmark technique using complete category discovery.
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