By Penelope Markellou, Maria Rigou, Spiros Sirmakessis (auth.), Dr. Spiros Sirmakessis (eds.)
ISBN-10: 3540250700
ISBN-13: 9783540250708
Text mining is an exhilarating program box and a space of medical examine that's presently below speedy improvement. It makes use of ideas from well-established clinical fields (e.g. info mining, computer studying, info retrieval, common language processing, case-based reasoning, statistics and information administration) so as to aid humans achieve perception, comprehend and interpret huge amounts of (usually) semi-structured and unstructured information. regardless of the advances made over the last few years, many matters stay unresolved.
Knowledge Mining attracts upon some of the key strategies of data administration, info mining and information discovery, meta-analysis and knowledge visualization. in the context of medical learn, wisdom mining is especially focused on the quantitative synthesis and visualization of analysis effects and findings.
The booklet offers effects from the applying of information mining ideas in quite a few quarter of the tutorial and indystrial study. the implications are elevated clinical figuring out in addition to advancements in study caliber and price. wisdom mining items can be utilized to spotlight learn possibilities, help with the presentation of "best" medical facts, facilitate learn portfolio administration, in addition to, facilitate coverage surroundings and selection making.
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Additional info for Knowledge Mining: Proceedings of the NEMIS 2004 Final Conference
Example text
An example of low integration and low personalized application is the implementation of a search engine with semantic browsing functionalities of the 46 S. Bolasco et al. Table 2. Solution Selection Strategy Model low Integration high Low A Standardisation C Internalisation Customisation High B Outsourcing D Synergism and Partnership Le Monde’s web site [26]. This engine presents the pertinent documents by automatic classification based on the extraction of correctly formed nominal groups from the text.
Table 1. Some main case studies by sector and application typology Understanding Text Mining: A Pragmatic Approach 33 34 S. Bolasco et al. (a) the possible types of results to be obtained; (b) the main specifications of the sectors of application; (c) the type of functions. The analysis of functions is crucial because it allows to understand and highlight main objectives of applications. 2 The Output of Text Mining The applications analysed present a considerable variety from the point of view of objectives, the type of tests analysed and the strategy of processing and analysis chosen.
In the banking and insurance Understanding Text Mining: A Pragmatic Approach 37 sectors, on the other hand, CRM applications are prevalent and aimed at improving the management of customer communication, by automatic systems of message re-routing and with QNL applications supporting the search engines asking questions in natural language. In the institutional field, ETL applications are prevalent for the filing and management of legal and normative documents and those of CRM and QLN are used to increase citizens’ participation and the dissemination of information.
Knowledge Mining: Proceedings of the NEMIS 2004 Final Conference by Penelope Markellou, Maria Rigou, Spiros Sirmakessis (auth.), Dr. Spiros Sirmakessis (eds.)
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