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 7 (2018)

Open Access Open Access  Restricted Access Subscription or Fee Access

Table of Contents


Effective ‘Strategic Implementation’ of Vendor-Managed Inventory (VMI) through Hierarchization of Identified Requisites: A Study with Automobile Sector of India PDF
Tarun Khatri, Mohd Shuaib, Dr. Sunil Luthra 137-142
An Improved Solution to Detect Credit Card Fraud Using Apache Hadoop in Big Data Environment PDF
V. Nivedha, R. Sankar 143-145
Analysis Study on Data Classification and Ranking for Sentimental Analysis in Data Mining PDF
M. Yuvaraja, S. Thavamani 146-152
Big Data in Banking for Marketers PDF
S.R Hiray, Karan Makode 153-155
Sentiment Analysis and Aspect Classification on Hotel Reviews PDF
B. Sandhiya, N. Shanthi, A. Thara Pearlly, S. Sumathi 156-159

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

ISSN: 0974 – 9578