Name
Abstract | ||
|---|---|---|
A method for filtering spam blogs (splogs) based on a machine learning technique, and its evaluation results are described. Today, spam blogs (splogs) became one of major issues on theWeb. The problem of splogs is that values of blog sites are different by people. We propose a novel user-oriented splog filtering method that can adapt each user's preference for valuable blogs. We use the SVM(Support Vector Machine) for creating a personalized splog filter for each user. We had two experiments: (1) an experiment of individual splog judgement, and (2) an experiment for user oriented splog filtering. From the former experiment, we found existence of 'gray' blogs that are needed to treat by persons. From the latter experiment, we found that we can provide appropriate personalized filters by choosing the best feature set for each user. An overview of proposed method, and evaluation results are described. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-16581-8_9 | BlogTalk |
Keywords | Field | DocType |
former experiment,appropriate personalized filter,support vector machine,personalized splog filter,evaluation result,machine learning,latter experiment,user-oriented splog,spam blogs,individual splog judgement,valuable blogs | Computer science,Judgement,Support vector machine,Filter (signal processing),User oriented,Feature set,Anchor text,Polynomial kernel,Artificial intelligence,Spam blog,Machine learning | Conference |
Volume | ISSN | ISBN |
6045 | 0302-9743 | 3-642-16580-X |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takayuki Yoshinaka | 1 | 10 | 1.34 |
| Soichi Ishii | 2 | 0 | 0.68 |
| Tomohiro Fukuhara | 3 | 130 | 17.73 |
| Hidetaka Masuda | 4 | 5 | 2.53 |
| Hiroshi Nakagawa | 5 | 390 | 40.38 |