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 8, No 10 (2016)
Table of Contents
|“Data Management Privacy Control in MongoDB”|
|Kusum Kakwani, Naziya Pathan, Shyam Dubey||295-298|
|Effective Vendor Managed Inventory (VMI) Implementation: Brief about Processes Involved and Requisites|
|Tarun Khatri, Sanjay Kumar, Abid Haleem||299-303|
|Chaos Genetic Algorithm and Adaboost Algorithm for Clustering the Data|
|Jenifer Mahilraj, Mesay Samuel, Amin Tuni Gure||304-306|
|A Novel k-Singular Value Decomposition Clustering Approach for Cancer Diagnosis|
|Dr. R. Anusuya, Dr. M. Mahalakshmi||307-310|
|Content Auditing in the Cloud Environment|
|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|
|Dr. Jyoti Pareek, Hardik Joshi, Krunal Chauhan, Rushikesh Patel||318-321|
This work is licensed under a Creative Commons Attribution 3.0 License.
ISSN: 0974 – 9578