Earticle

초록

영어

With the rapid growth of personal website influence, the advertisement placing has become an important investment in personal websites. But in order to accurate the advertisement placing, the specific quest for the specific users with their specific interesting need to be concerned. Acquiring, preprocessing and classifying consumption intention of the released information that published in the personal websites is the main task of this essay. We regard consumption intention mining as a binary classification problem, and extract multi-dimensional features from the raw corpus. Finally, we propose models based on SVM, Naïve Bayes and deep learning to solve the consumption intention classification problem. The experimental result shows that the deep learning based method achieves the highest F-measure.

목차

Abstract
 1. Introduction
 2. Intent Analysis and SVM Classification Theory
 3. Classification model for Intent Mining based on SVM
  3.1 The Fusion of Multiple Attribute based on SVM
  3.2 Classification Model of Intent Mining based on Fusion Multiple Attributes based on SVM
 4. Experiment
 5. Conclusion
 Acknowledgement
 Reference

키워드

저자

• Shuang Zhang [ School of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, PR China ]
• Nianbin Wang [ School of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, PR China ]

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