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


No announcements have been published.
More Announcements...

Vol 8, No 10 (2016)

Open Access Open Access  Restricted Access Subscription or Fee Access

Table of Contents


“Data Management Privacy Control in MongoDB” PDF
Kusum Kakwani, Naziya Pathan, Shyam Dubey 295-298
Effective Vendor Managed Inventory (VMI) Implementation: Brief about Processes Involved and Requisites PDF
Tarun Khatri, Sanjay Kumar, Abid Haleem 299-303
Chaos Genetic Algorithm and Adaboost Algorithm for Clustering the Data PDF
Jenifer Mahilraj, Mesay Samuel, Amin Tuni Gure 304-306
A Novel k-Singular Value Decomposition Clustering Approach for Cancer Diagnosis PDF
Dr. R. Anusuya, Dr. M. Mahalakshmi 307-310
Content Auditing in the Cloud Environment PDF
R. Emad El-Dein, B. Youssef, S. ElGamal 311-317
Experiments with Different Indexing Techniques for Text Retrieval tasks on Gujarati Language using Bag-of-Words Approach PDF
Dr. Jyoti Pareek, Hardik Joshi, Krunal Chauhan, Rushikesh Patel 318-321

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

ISSN: 0974 – 9578