Sciweavers

SDM
2008
SIAM
135views Data Mining» more  SDM 2008»
13 years 6 months ago
A Spamicity Approach to Web Spam Detection
Web spam, which refers to any deliberate actions bringing to selected web pages an unjustifiable favorable relevance or importance, is one of the major obstacles for high quality ...
Bin Zhou 0002, Jian Pei, ZhaoHui Tang
CIKM
2008
Springer
13 years 6 months ago
Predicting web spam with HTTP session information
Web spam is a widely-recognized threat to the quality and security of the Web. Web spam pages pollute search engine indexes, burden Web crawlers and Web mining services, and expos...
Steve Webb, James Caverlee, Calton Pu
AIRWEB
2008
Springer
13 years 6 months ago
Exploring linguistic features for web spam detection: a preliminary study
We study the usability of linguistic features in the Web spam classification task. The features were computed on two Web spam corpora: Webspam-Uk2006 and Webspam-Uk2007, we make t...
Jakub Piskorski, Marcin Sydow, Dawid Weiss
AIRWEB
2008
Springer
13 years 6 months ago
Identifying web spam with user behavior analysis
Combating Web spam has become one of the top challenges for Web search engines. State-of-the-art spam detection techniques are usually designed for specific known types of Web spa...
Yiqun Liu, Rongwei Cen, Min Zhang, Shaoping Ma, Li...
AIRWEB
2008
Springer
13 years 6 months ago
Web spam identification through content and hyperlinks
We present an algorithm, witch, that learns to detect spam hosts or pages on the Web. Unlike most other approaches, it simultaneously exploits the structure of the Web graph as we...
Jacob Abernethy, Olivier Chapelle, Carlos Castillo
CEAS
2006
Springer
13 years 8 months ago
Introducing the Webb Spam Corpus: Using Email Spam to Identify Web Spam Automatically
Just as email spam has negatively impacted the user messaging experience, the rise of Web spam is threatening to severely degrade the quality of information on the World Wide Web....
Steve Webb, James Caverlee, Calton Pu
CIKM
2009
Springer
13 years 8 months ago
A co-classification framework for detecting web spam and spammers in social media web sites
Social media are becoming increasingly popular and have attracted considerable attention from spammers. Using a sample of more than ninety thousand known spam Web sites, we found ...
Feilong Chen, Pang-Ning Tan, Anil K. Jain
WEBDB
2004
Springer
100views Database» more  WEBDB 2004»
13 years 10 months ago
Spam, Damn Spam, and Statistics: Using Statistical Analysis to Locate Spam Web Pages
The increasing importance of search engines to commercial web sites has given rise to a phenomenon we call “web spam”, that is, web pages that exist only to mislead search eng...
Dennis Fetterly, Mark Manasse, Marc Najork
ICDM
2006
IEEE
139views Data Mining» more  ICDM 2006»
13 years 10 months ago
Detecting Link Spam Using Temporal Information
How to effectively protect against spam on search ranking results is an important issue for contemporary web search engines. This paper addresses the problem of combating one majo...
Guoyang Shen, Bin Gao, Tie-Yan Liu, Guang Feng, Sh...
CEAS
2007
Springer
13 years 10 months ago
Characterizing Web Spam Using Content and HTTP Session Analysis
Web spam research has been hampered by a lack of statistically significant collections. In this paper, we perform the first large-scale characterization of web spam using conten...
Steve Webb, James Caverlee, Calton Pu