Earticle

초록

영어

During the last two decades, a substantial amount of research efforts has been intended for support vector machine at the application of various data mining tasks. Data Mining is a pioneering and attractive research area due to its huge application areas and task primitives. Support Vector Machine (SVM) is playing a decisive role as it provides techniques those are especially well suited to obtain results in an efficient way and with a good level of quality. In this paper, we survey the role of SVM in various data mining tasks like classification, clustering, prediction, forecasting and others applications. In broader point of view, we have reviewed the number of research publications that have been contributed in various internationally reputed journals for the data mining applications and also suggested a possible no. of issues of SVM. The main aim of this paper is to extrapolate the various areas of SVM with a basis of understanding the technique and a comprehensive survey, while offering researchers a modernized picture of the depth and breadth in both the theory and applications.

목차

Abstract
 1. Introduction
 2. Support Vector Machine
 3. Literature Review
 4. Analytical Discussions, Limitations & Suggestions
 5. Concluding Remarks
 Acknowledgements
 References

키워드

저자

• Janmenjoy Nayak [ Department of Computer Science Engg. & Information Technology Veer Surendra Sai University of Technology, Burla - 768018, Odisha, India ]
• Bighnaraj Naik [ Department of Computer Science Engg. & Information Technology Veer Surendra Sai University of Technology, Burla - 768018, Odisha, India ]
• H. S. Behera [ Department of Computer Science Engg. & Information Technology Veer Surendra Sai University of Technology, Burla - 768018, Odisha, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605