Dead Link Prediction Model Based on Double SVM
- DOI
- 10.2991/meic-15.2015.60How to use a DOI?
- Keywords
- dead link; Support Vector Machine; the effective attributes;Dead Link Prediction Model;the independent model
- Abstract
All the search engines are facing the problem of dead link. Dead link prediction model, which is able to quickly distinguish between normal links and dead links, filter out dead links, ensure the validity of the search results. This paper proposed to construct the SVM dead link prediction model by the effective attributes of the links because the fast update of the links in engine library, this model can quickly identify dead links. Due to the attributes related to the types of web site, independent training prediction model was proposed according to the different types of web site to improve the precision rate, experiments proved that the precision and recall rate of the independent model higher than the uniform model. It is unrealistic that training samples marked completely rely on manual because the independent training samples’ amount is large, so using SVM dead link prediction model based on web content to prepare the sample because it’s high accuracy, and applicable to all links. It constituted a dead link prediction model based on double SVM by using SVM dead link prediction model twice, which greatly improved the precision rate of dead link prediction, and reduces the prediction time.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Honglan Liu AU - Xiaona Qin AU - Yong He PY - 2015/04 DA - 2015/04 TI - Dead Link Prediction Model Based on Double SVM BT - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering PB - Atlantis Press SP - 252 EP - 256 SN - 2352-5401 UR - https://doi.org/10.2991/meic-15.2015.60 DO - 10.2991/meic-15.2015.60 ID - Liu2015/04 ER -