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Keyword-based content alert services, e.g., Google Alerts and Microsoft Live Alerts, empower the end users with the ability to automatically receive useful and most recent content. In this paper, we leverage the favorable properties of DHTs, such as scalability, and propose a design of a scalable keyword-based content
As a promising web application paradigm, web services have been widely adopted as e-business solutions. However, UDDI, the discovery mechanism of Web services, has the limitation of lack of semantic inference support, and the search mechanism based on keyword and categorization information leads to a limited
semantic enrichment of the media has allowed implement an improved search service, which attempts to overcome the limitations of traditional engines based on matching keywords.
as titles, abstracts, keywords and the Chinese Library Classification Codes (CLCCs). According to the reviewer's interest model, we then propose a recommendation approach, which can send a paper published online to the reviewers that are experts in the scoop of the paper. Experimental results show that our
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