The Electronic Journal of Knowledge Management publishes original articles on topics relevant to studying, implementing, measuring and managing knowledge management and intellectual capital.

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Journal Issue
Volume 14 Issue 3 / Aug 2016  pp113‑190

Editor: Vincent Ribiere

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Editorial  pp113‑114

Vincent Ribiere

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Taking a Knowledge Perspective on Needs: Presenting Two Case Studies Within an Educational Environment in Austria  pp115‑127

Alexander Kaiser, Florian Kragulj, Thomas Grisold

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Mining Knowledge of the Patient Record: The Bayesian Classification to Predict and Detect Anomalies in Breast CancerŽ  pp128‑139

Souad Demigha

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Abstract: knowledge management, data mining, and text mining techniques have been adopted in various successful biomedical applications in recent years. Data Mining (DM) is the most important subfields in knowledge management (KM). It has been proven that data mining can enhance the KM process with better knowledge. In this paper, we investigate the application of DM techniques for mining knowledge of the patient record. The patient record represents documents of the patients examinations and treatments. Data Mining is the process of miningŽ or extracting information from a data set and transform it into an understandable structure for further use. We propose a methodology for mining medical knowledge based on the Bayesian Classification to predict and detect anomalies in breast cancer. We use the Naïve Bayes Algorithm to develop this methodology. We illustrate the knowledge mining process by real examples of medical field. We investigate through these illustrations how knowledge is better mined and thus, reused when applying concepts and techniques of Data Mining. On the other hand, we investigate the potential contribution of the Naive Bayesian Classification methodology as a reliable support in computer‑aided diagnosis of such events, using the well‑known Wisconsin Prognostic Breast Cancer dataset. Finally, we will demonstrate the suitability and ability of the Naive Bayes methodology in Classification/Prediction problems in breast cancer. 


Keywords: Keywords: Patient Record, Data Mining, Bayesian Classification, Naïve Bayes Algorithm, Breast cancer prediction


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An Analysis of Knowledge Management Lifecycle Frameworks: Towards a Unified Framework  pp140‑153

Mzwandile Muzi Shongwe

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Antecedents of Successful Collaboration in Community of Practice between Academia and Industry: A Case Study  pp154‑165

Ilpo Pohjola, Anu Puusa, Päivi Iskanius

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A Theoretical Model to Integrate PKM with Kolbs Learning Model for Mitigating Risks From Exhaustive Internet Exposures  pp166‑176

Ben Fong, Man Fung Lo, Artie Ng

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The Inventive output, of an Effective implementation of Knowledge and Performance Management Perspectives  pp177‑190

Pieris Chourides, Lycourgos Hadjiphanis, Loukia Ch. Evripidou

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