Data Mining and Knowledge Engineering

CiiT International Journal of Data Mining and Knowledge Engineering


        The aim of Journal Data Mining Knowledge Engineering focuses on theoretical and practical research development on knowledge engineering and data mining.


        The scope of the journal includes developing technologies in Data Analysis, Data cleaning and pre-processing, Data engineering, Data extraction and reporting, Data mining algorithms and processes, Data mining techniques, tools and applications, Decision analysis, Knowledge-based/rule-based/case based/expert system design, Knowledge acquisition, dissemination, discovery methodologies and technologies, Database design and architecture, Intelligent system design, Data integration and exchange, Data security and data integrity, Database administration and maintenance issues.

Print: ISSN 0974 – 9683 & Online: ISSN 0974 – 9578


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Vol 10, No 2 (2018)

Open Access Open Access  Restricted Access Subscription or Fee Access

Table of Contents


A Survey of IoT Based Smart Cities PDF
G. Deepalakshmi, K. Sakthi Subramaniam, S. Subramani 21-24
Big Data Hadoop: A Survey on Security Issues, Challenges and Solutions PDF
S. Rajarajesware, Dr. H. Abdul Rauf, Dr. S. P. Victor 25-27
Overview of Big Data Analytics System for Storing and Processing Huge Data PDF
S. Natarajan, Dr. H. Abdul Rauf, Dr. S. P. Victor 28-30
An Appraisal and Proportional Study of Data Mining Techniques for Web Intrusion Detection Methods PDF
S. Lakshmi Devi, S. P. Priyadharshini 31-34
Improved Energy Utilization within Smart Grid PDF
G. Ramya, M. Gokul, G. Janarthanan, S. Salman Faris, N. Yukesh 35-39

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This work is licensed under a Creative Commons Attribution 3.0 License.

ISSN: 0974 – 9578