Link Variable TrustRank for Fighting Web Spam

2008 ◽  
Author(s):  
Qi Chen ◽  
Song-Nian Yu ◽  
Sisi Cheng
Keyword(s):  
Web Spam ◽  
Link Variable

Construction and Reduction Methods of Web Spam Identification Index System

2019 ◽  
Vol 12 (3) ◽  
pp. 202-211
Author(s):  
Yuancheng Li ◽  
Rong Huang ◽  
Xiangqian Nie
Keyword(s):  
Index System ◽  
Rapid Development ◽  
Recognition Rate ◽  
Computing Power ◽  
Detection Model ◽  
Web Spam ◽  
Reduction Methods ◽  
Massive Scale ◽  
The Index System ◽  
The Web

Background: With the rapid development of the Internet, the number of web spam has increased dramatically in recent years, which has wasted search engine storage and computing power on a massive scale. To identify the web spam effectively, the content features, link features, hidden features and quality features of web page are integrated to establish the corresponding web spam identification index system. However, the index system is highly correlation dimension. Methods: An improved method of autoencoder named stacked autoencoder neural network (SAE) is used to realize the reduction of the web spam identification index system. Results: The experiment results show that our method could reduce effectively the index of web spam and significantly improves the recognition rate in the following work. Conclusion: An autoencoder based web spam indexes reduction method is proposed in this paper. The experimental results show that it greatly reduces the temporal and spatial complexity of the future web spam detection model.

A reference collection for web spam

2006 ◽  
Vol 40 (2) ◽  
pp. 11-24 ◽  
Author(s):  
Carlos Castillo ◽  
Debora Donato ◽  
Luca Becchetti ◽  
Paolo Boldi ◽  
Stefano Leonardi ◽  
...  
Keyword(s):  
Web Spam ◽  
Reference Collection

scholarly journals Countering Web Spam of Link-based Ranking Based on Link Analysis

2011 ◽  
Vol 23 ◽  
pp. 310-315 ◽  
Author(s):  
Hongwei Wang ◽  
Yuankai Li ◽  
Kaiqiang Guo
Keyword(s):  
Link Analysis ◽  
Web Spam

Cross-lingual web spam classification

2013 ◽  
Author(s):  
András Garzó ◽  
Bálint Daróczy ◽  
Tamás Kiss ◽  
Dávid Siklósi ◽  
András A. Benczúr
Keyword(s):  
Web Spam ◽  
Cross Lingual

scholarly journals Comparative Study of Web Spam Detection using Data Mining

2013 ◽  
Vol 68 (18) ◽  
pp. 26-29
Author(s):  
Chirag Nathwani ◽  
Viralkumar Prajapati ◽  
Deven Agravat
Keyword(s):  
Data Mining ◽  
Comparative Study ◽  
Spam Detection ◽  
Web Spam ◽  
Using Data

scholarly journals Web Spam Detection by Learning from Small Labeled Samples

2012 ◽  
Vol 50 (21) ◽  
pp. 1-5 ◽  
Author(s):  
Jaber Karimpour ◽  
Ali A. Noroozi ◽  
Somayeh Alizadeh
Keyword(s):  
Spam Detection ◽  
Web Spam

scholarly journals Avaliação de Desempenho de Métodos de Classificação Aplicados na Identificação de Spam Hosts

2012 ◽  
Vol 5 ◽  
Author(s):  
Renato Moraes Silva ◽  
Alex Garcia Vaz ◽  
Tiago Agostinho Almeida ◽  
Akebo Yamakami
Keyword(s):  
Web Spam

A web vem se tornando cada vez mais importante para seus usuários, tanto como fonte de diversão, comunicação, pesquisa, notícias e comércio. Consequentemente, os sites concorrem entre si para atrair a atenção dos usuários, sendo que muitos ganham maior visibilidade através de estratégias que enganam os motores de busca. Esses sites, conhecidos como web spam, causam prejuízos pessoais e econômicos aos usuários. Diante desse cenário, este trabalho apresenta uma análise de desempenho de diversas técnicas de aprendizagem de máquina aplicadas na detecção automática de servidores web que propagam web spam. Por meio de uma validação estatística dos resultados observou-se as técnicas de bagging de árvores de decisão, redes neurais perceptron de múltiplas camadas, floresta aleatória e boosting adaptativo de árvores de decisão são promissoras na tarefa de detecção de spam hosts.

scholarly journals Analysis of Web Spam for Non-English Content: Toward More Effective Language-Based Classifiers

PLoS ONE ◽  
2016 ◽  
Vol 11 (11) ◽  
pp. e0164383 ◽  
Author(s):  
Mansour Alsaleh ◽  
Abdulrahman Alarifi
Keyword(s):  
Web Spam
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