International Journal of Advance Computational Engineering and Networking (IJACEN)
Follow Us On :
current issues
Volume-11,Issue-8  ( Aug, 2023 )
Past issues
  1. Volume-11,Issue-7  ( Jul, 2023 )
  2. Volume-11,Issue-6  ( Jun, 2023 )
  3. Volume-11,Issue-5  ( May, 2023 )
  4. Volume-11,Issue-4  ( Apr, 2023 )
  5. Volume-11,Issue-3  ( Mar, 2023 )
  6. Volume-11,Issue-2  ( Feb, 2023 )
  7. Volume-11,Issue-1  ( Jan, 2023 )
  8. Volume-10,Issue-12  ( Dec, 2022 )
  9. Volume-10,Issue-11  ( Nov, 2022 )
  10. Volume-10,Issue-10  ( Oct, 2022 )

Statistics report
Nov. 2023
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 128
Paper Published : 1530
No. of Authors : 3973
  Journal Paper

Paper Title :
Data Mining In Mobile Environment-An Overview

Author :R. R. Shelke, R. V. Dharaskar, V. M. Thakare

Article Citation :R. R. Shelke ,R. V. Dharaskar ,V. M. Thakare , (2015 ) " Data Mining In Mobile Environment-An Overview " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 66-69, Volume-3,Issue-12

Abstract : Mobile data mining is a very promising area for users and professionals where users, resource and applications are mobile. On the basis of researcher’s experience, it can be suggested that the combined use of a service oriented approach with mobile programming technologies makes easier implementation of mobile knowledge discovery applications. Data mining services play an important role in the field of Communication industry. Data mining is also called knowledge discovery in several database including mobile databases. In this paper, consumptive behavior based on data mining technology is discussed and analyzed. Different aspects of data mining techniques and their behavior is discussed and analyzed in mobile environment. Due to recent advances in computer hardware technology, a vast number of mobile clients are accessing various information systems via wireless communication from anywhere at any time. At present, the wireless services do not support the personalization and localization for mobile clients. If wireless internet service provider (WISP) has the ability to explore the user behaviour, and support Location-based Services (LBS), it will increase the client's loyalties and satisfaction. In this paper, the use of data mining technologies to trace out the mobile clients’ behaviours and the sequences of service requests is studied. Keywords- Data Mining, Mobile Data Mining.

Type : Research paper

Published : Volume-3,Issue-12


Copyright: © Institute of Research and Journals

| PDF |
Viewed - 93
| Published on 2015-12-15
IRAJ Other Journals
IJACEN updates
Paper Submission is open now for upcoming Issue.
The Conference World