Relevancy in Knowledge Retrieval with a Data-mining technique - Kallimani, Vishweshwar;Isa, Dino
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Retrieving the required information to troubleshoot a particular problem from a Case-base (Knowledge Management System database), containing conceptual and highly technical information can be a challenging task for an inexperienced person. Conventional matching algorithms give a bigger set of matched results that may contain irrelevant cases. This may cause difficulty for an inexperienced person to distinguish between the relevant and non-relevant information. This book presents an enhanced method for retrieval of stored semiconductor process engineering problems and the corresponding…mehr

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Produktbeschreibung
Retrieving the required information to troubleshoot a particular problem from a Case-base (Knowledge Management System database), containing conceptual and highly technical information can be a challenging task for an inexperienced person. Conventional matching algorithms give a bigger set of matched results that may contain irrelevant cases. This may cause difficulty for an inexperienced person to distinguish between the relevant and non-relevant information. This book presents an enhanced method for retrieval of stored semiconductor process engineering problems and the corresponding solutions. This textbook is focused on the retrieval of wire-bond (WB) related knowledge (in Semi-Conductor Industry)on the Case based reasoning platform, with Unsupervised Learning Neural network - SOM (Self Organizing maps) technique.
Autorenporträt
Dr Vish Kallimani has obtained Ph. D. in Computer Science from the University of Nottingham,and M.Engg (Electronics & Comm) from Birla Institute of Technology, India. He has been awarded as a HEA Fellow, UK in 2010. His area of specialization is in un-supervised machine learning and knowledge management.