earticle

논문검색

A Comprehensive Survey on Support Vector Machine in Data Mining Tasks : Applications & Challenges

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

저자정보

  • 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

자료제공 : 네이버학술정보

    ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

    0개의 논문이 장바구니에 담겼습니다.