- Title
- Using links to aid web classification
- Creator
- Xie, Wei; Mammadov, Musa; Yearwood, John
- Date
- 2007
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/54826
- Identifier
- vital:3631
- Identifier
-
https://doi.org/10.1109/ICIS.2007.191
- Identifier
- ISBN:0769528414
- Abstract
- In this paper, we will present a new approach of using link information to improve the accuracy and efficiency of web classification. However, different from others, we only use the mappings between linked documents and their own class or classes. In this case, we only need to add a few features called linked-class features into the datasets. We apply SVM and BoosTexter for classification. We show that the classification accuracy can be improved based on mixtures of ordinary word features and out-linked-class features. We analyze and discuss the reason of this improvement.
- Publisher
- Melbourne, Victoria : IEEE
- Relation
- Paper presented at 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007, Melbourne, Victoria : 11th-13th July 2007 p. 981-986
- Rights
- Copyright IEEE
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 08 Information and Computing Sciences; Internet; Classification; Support vector machines; Text analysis
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