Name
Abstract | ||
|---|---|---|
Recent research on web spam detection has shown promising results, and many new and efficient detection algorithms have been developed. While most research focuses on developing algorithms, our investigation shows that the features used in the algorithms are in fact very important, and different features can lead to very different results. This paper investigates three types of web spam, content-based, link-based and cloaking, and introduces new features for identifying the three types of spam. Our experimental results show that the introduction of new features significantly improves the detection performance. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICTAI.2016.0096 | 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) |
Keywords | Field | DocType |
Web Spam Detection,Content-based Spam Features,Link-based Spam Features,Cloaking Spam Features | Cloaking,Search engine,Web page,Information retrieval,Computer science,Feature extraction,Artificial intelligence,Machine learning,Benchmark (computing),Spamdexing | Conference |
ISSN | ISBN | Citations |
1082-3409 | 978-1-5090-4460-3 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Santosh Kumar | 1 | 7 | 1.86 |
| Xiaoying Gao | 2 | 220 | 32.95 |
| Ian S. Welch | 3 | 120 | 18.53 |