Home / Journals American Journal of Data Mining and Knowledge Discovery / Privacy Preservation in Data Mining and Knowledge Discovery
Privacy Preservation in Data Mining and Knowledge Discovery
Submission DeadlineJan. 10, 2020

Submission Guidelines: http://www.sciencepublishinggroup.com/home/submission

Lead Guest Editor
Dr.v.shyamala susan
Department of Computer Science, A.P.C. Mahalaxmi College for Women, Manonmanium Sundaranar University, tuticorin, tamilnadu, India
Guest Editors
  • Suresh Shanmugasundaram
    Faculty of Engineering & Applied Sciences, Botho University, Gaborone, Botswana
  • Dr.S.Chidambara Nathan
    MCA Department, St. Xavier's College, Palayamkottai, India
  • A. Amuthan
    Department of Computer Science & Engineering, Pondicherry Engineering College, Pondicherry, India
  • Juliana Sunil
    Department of Information Technology, Rathinam college of arts and science, Bharathiar University, Coimbatore, India
  • Sankari Sankaran
    Department of Chemistry, A.P.C Mahalaxmi College for Women, Thoothukudi, Tamilnadu, India
Data mining and knowledge discovery in recent research needs a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. The collection and analysis of data are continuously growing due to the prevalence of computing devices. The analysis of such information is needed for developing businesses and to the society in different fields.
This Special Issue will mainly focus on the information and knowledge analysis, as well as the extraction of the inherited knowledge. And this will also focus on extracting knowledge by incorporating it into smart tools and applications. Rapid growing of information technologies nowadays has brought wonderful opportunities for data sharing and integration, and also demands for privacy protection. Privacy-preserving data mining techniques assure data privacy without compromising the confidentiality and quality of data. Although many techniques have been developed, many of the key problems still remain open in this area. Hence this special issue will also aims to provide an opportunity for presenting recent advances as well as new research directions in all issues related to privacy-preserving data mining.
In this special issue, Scientists/Researchers/Students/Other Scholar are invited, to submit their original research, case study, survey paper or extensive review articles.
Aims and Scope:
  1. Data mining and machine learning applied to information extraction
  2. Knowledge base maintenance using Machine Learning and Data Mining
  3. Security and semantic issues and technologies for knowledge discovery and sharing
  4. Data mining techniques for mining and analyzing software repositories
  5. Information Retrieval techniques for mining and analyzing software repositories
  6. Knowledge Discovery and Extraction
  7. Mining fields: Data Mining, Text Mining, Cloud Mining, Web Mining
  8. Information Extraction and Retrievals
  9. Privacy-preserving data mining
  10. Privacy-preserving Information Retrieval
  11. Trust management for information mining
  12. Inference/disclosure related information mining
  13. Privacy enhancement technologies in web environments
  14. Privacy policy analysis
  15. Privacy-preserving data integration
  16. Privacy policy infrastructure
  17. Data mining for security and privacy
  18. Computational intelligence in security and privacy
  19. Intrusion, anomaly and fraud detection
  20. Data-driven access control
  21. Secure cloud computing
  22. Secure multi-party computation
  23. Data privacy
  24. Sensitive data collection
Guidelines for Submission
Manuscripts should be formatted according to the guidelines for authors
(see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=603).

Please download the template to format your manuscript.

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