International Journal of Knowledge Engineering and Data Mining
- Editor in Chief
- Prof. Dr. Madjid Tavana
- ISSN online
- ISSN print
- 4 issues per year
IJKEDM publishes theoretical and practical research development on knowledge engineering and data mining. The journal is devoted to techniques and skills used for knowledgebase systems or intelligent applications development, including all areas of data architecture, data integration and data exchange, data mining, knowledge acquisition, representation, dissemination, codification and discovery techniques, and their technologies. It also focuses on their applications and case studies in industrial, medical and business sectors.
Topics covered include
- Ontology engineering
- Knowledge representation techniques
- Knowledge retrieval
- Text mining
- Knowledge-based/rule-based/case-based/expert system design
- Knowledge acquisition, dissemination, discovery methodologies and technologies
- Algorithms for data mining
- Data models
- Database design and architecture
- Intelligent system design
- Data integration and exchange
- Data security and data integrity
- Database administration and maintenance issues
- Applications and case studies
The objectives of IJKEDM are to establish an effective channel of communication between managers, users, knowledge engineers, IT professionals, medical informaticians, academic and research institutions and persons concerned with the development knowledgebase systems and intelligent applications. It also aims to promote and coordinate developments in the field of knowledge engineering and data mining. IJKEDM aims to highlight theoretical and practical research in data analysis architectures, models, methodologies, techniques and technologies in knowledge engineering and data mining, and their application.
IJKEDM provides a vehicle to help business analysts, knowledge engineers, IT professionals, medical informaticians, academics and researchers to disseminate information and to learn from each other's work. Readers will be able to learn and obtain techniques and skills in knowledge engineering and data mining. Readers will learn future directions and research development in data analysis, data integration and exchange, data mining techniques, knowledge acquisition, representation and discovery in knowledgebase system, and their applications.
IJKEDM is devoted to the publications of high quality papers on theoretical developments and practical applications in knowledge engineering and data mining. The journal publishes original papers, state-of-the-art reviews, technical reports and case studies. Special issues devoted to current issues in knowledge engineering and data mining will occasionally be published.
IJKEDM is indexed in:
- Academic OneFile (Gale)
- ACM Digital Library
- Asian Digital Library
- cnpLINKer (CNPIEC)
- DBLP Computer Science Bibliography
IJKEDM is listed in:
Editor in Chief
- Tavana, Madjid, La Salle University, USA
- Connolly, Regina, Dublin City University, Ireland
- Kong, Ming Hei, Hong Kong Institute of Vocational Education, Hong Kong SAR, China
- Lui, Willie, Carrier HK Ltd, Hong Kong SAR, China
- Rinaldi, Antonio M., University of Naples Federico II, Italy
Editorial Board Members
- Arabnia, Hamid R., University of Georgia, USA
- Davis, Joseph, The University of Sydney, Australia
- Dumka, Ankur, University of Petroleum and Energy Studies, India
- Ebrahimpour, Maling, University of Rhode Island, USA
- Eyob, Ephrem, Virginia State University, USA
- Hsu, Wynne, National University of Singapore, Singapore
- Kijima, Kyoichi Jim, Tokyo Institute of Technology, Japan
- Lau, Adela S.M., The Hong Kong University of Science and Technology, Hong Kong SAR, China
- Lee, Chi-Guhn, University of Toronto, Canada
- Lee, Jay, University of Cincinnati, USA
- Li, Jinyan, Nanyang Technological University, Singapore
- Lin, Binshan, Louisiana State University in Shreveport, USA
- Lu, Jye-Chyi (JC), Georgia Institute of Technology, USA
- Mastorakis, Nikos, Hellenic Naval Academy, Greece
- Nakamor, Yoshiteru, Japan Advanced Institute of Science and Technology, Japan
- Patrick, Brézillon, Pierre et Marie Curie University, France
- Song, William Wei, Dalarna University, Sweden
A few essentials for publishing in this journal
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- Briefs and research notes are not published in this journal.
- All our articles go through a double-blind review process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
- There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
- All articles for this journal must be submitted using our online submissions system.
- Submit here.
Text mining the presidency
3 August, 2018
A new text mining technique has been developed by US researchers. The system works in two stages. Firstly, it uses a statistical tool known as a naive Bayes classifier, a supervised machine-learning algorithm to train for classes. Secondly, it uses k-means analysis, an unsupervised machine-learning algorithm to determine what categories are emerging from the mentions of each class [...]More details...