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utilizes text-mining, Web service technologies and domain knowledge, in order to extract keywords, to retrieve related records from an external source, and to filter the extracted keywords list. This study meets a practical challenge encountered at the School of Veterinary and Biomedical Sciences at Murdoch University. The
proposed solution in this paper involves text-mining (keyword extraction) and web service technologies for enhancing the existing results and to provide a comprehensive set of information related to local clinical records from the internal database.
This paper presents a case study of an image retrieval system based on a notion of similarity between images in a multimedia database and where a user request can be an image file or a keyword. The CBIR (content based image retrieval) system, the current system of search for information (SSI) -e.g. PEIR, MIRC, MIR
graph formation framework and (2). a preliminary analysis of retweet graphs and associated diffusion metrics for health tweets. Given the ambiguous nature (due to polysemy and sarcasm) of health relatedness of tweets collected with keyword based matches, our initial study is limited to « 200 health related tweets
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.