395 Hits in 3.2 sec

Transductive link spam detection

Dengyong Zhou, Christopher J. C. Burges, Tao Tao
2007 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web - AIRWeb '07  
Since linkage information is widely used in web search, link-based spamming has also developed. So far, many techniques have been proposed to detect link spam.  ...  We have applied the approach to real-world link spam detection problems, and encouraging results have been obtained.  ...  Algorithm 1 Transductive Link Spam Detection Given a web graph G = (V, E), some web pages S ⊂ V have been manually labeled as normal or spam. We assume the graph to be strongly connected.  ... 
doi:10.1145/1244408.1244413 fatcat:hldvesjog5bizou2lggonklhs4

Adversarial Information Retrieval on the Web (AIRWeb 2007)

Carlos Castillo, Kumar Chellapilla, Brian D. Davison
2008 SIGIR Forum  
Krysta Svore took the stage again, this time to talk about "Transductive Link Spam Detection."  ...  Masashi Toyoda presented "A Large-Scale Study of Link Spam Detection by Graph Algorithms."  ... 
doi:10.1145/1394251.1394267 fatcat:ywd3ygzofbbjtbwxshwgu3opy4

EGGS: A Flexible Approach to Relational Modeling of Social Network Spam [article]

Jonathan Brophy, Daniel Lowd
2020 arXiv   pre-print
Furthermore, spammers disguise their messages to look legitimate, tricking users into clicking on links and tricking spam filters into tolerating their malicious behavior.  ...  In this paper, we present Extended Group-based Graphical models for Spam (EGGS), a general-purpose method for classifying spam in online social networks.  ...  Spam Detection Performance (AUPR) Inductive Inductive + Transductive Model SoundCloud YouTube Twitter SoundCloud YouTube Twitter Limited Independent 0.396 0.148 0.260 0.352 0.387 0.466 SGL  ... 
arXiv:2001.04909v2 fatcat:7igd66tsm5bzjpjpadgcq6itce

Two-view Transductive Support Vector Machines [chapter]

Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
2010 Proceedings of the 2010 SIAM International Conference on Data Mining  
We applied our two-view transductive SVM to the WebKB course dataset, and a reallife review spam classification dataset.  ...  Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam detection, which changes  ...  In particular, it was motivated by our need to detect spam product reviews from online forums.  ... 
doi:10.1137/1.9781611972801.21 dblp:conf/sdm/LiHC10 fatcat:jdibsuy6jvhxjnnxkrknkz44dm

Designing a Web Spam Classifier Based on Feature Fusion in the Layered Multi-Population Genetic Programming Framework

2013 Advances in Distributed Computing and Artificial Intelligence Journal  
This paper employs the recently proposed Layered Multi-population Genetic Programming model for Web spam detection task as well application of correlation coefficient analysis for feature space reduction  ...  Nowadays, Web spam pages are a critical challenge for Web retrieval systems which have drastic influence on the performance of such systems.  ...  [ZHOU, D. et al. 2007] with transductive link spam detection. The third series of Web spam detection techniques are combinative methods.  ... 
doi:10.14201/adcaij2014261527 doaj:c8746dcdb7a441e6b64e27014fc1e58c fatcat:q7u4yl252zfgvc4v3gm7mho7qu

Web spam identification through content and hyperlinks

Jacob Abernethy, Olivier Chapelle, Carlos Castillo
2008 Proceedings of the 4th international workshop on Adversarial information retrieval on the web - AIRWeb '08  
We present an algorithm, witch, that learns to detect spam hosts or pages on the Web.  ...  The method is efficient, scalable, and provides state-of-the-art accuracy on a standard Web spam benchmark.  ...  It also includes 2 recent state-of-the-art methods for web spam detection, stacked graphical learning [6] and transductive link spam proposed in [17] , which uses only hyperlinks and not content based  ... 
doi:10.1145/1451983.1451994 dblp:conf/airweb/AbernethyCC08 fatcat:awpcoile4fc7dl3ms77sfk3uee

Semi-supervised spam filtering using aggressive consistency learning

Mona Mojdeh, Gordon V. Cormack
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
Our results compare favorably with the best-known methods, using as few as just two labeled examples: one spam and one non-spam.  ...  The motivating application of this method is spam filters with access to very few labeled message.  ...  The same method is applied for detecting web spam in [3] .  ... 
doi:10.1145/1835449.1835598 dblp:conf/sigir/MojdehC10 fatcat:eizafhyfl5gxfddb4nk6onp4qe

Spectral clustering and transductive learning with multiple views

Dengyong Zhou, Christopher J. C. Burges
2007 Proceedings of the 24th international conference on Machine learning - ICML '07  
We consider spectral clustering and transductive inference for data with multiple views.  ...  We further build multiview transductive inference on the basis of multiview spectral clustering. Our framework leads to a mixture of Markov chains defined on every graph.  ...  Spam detection is a highly unbalanced classification problem. In our dataset, only 5.3% hosts are spam.  ... 
doi:10.1145/1273496.1273642 dblp:conf/icml/ZhouB07 fatcat:loidkj3l3rc47pkdqxzd6tzxim

Robust PageRank and locally computable spam detection features

Reid Andersen, Christian Borgs, Jennifer Chayes, John Hopcroft, Kamal Jain, Vahab Mirrokni, Shanghua Teng
2008 Proceedings of the 4th international workshop on Adversarial information retrieval on the web - AIRWeb '08  
Various link-based features of web pages have been introduced and have proven effective at identifying link spam.  ...  In this paper, we describe several linkbased spam-detection features, both supervised and unsupervised, that can be derived from these approximate supporting sets.  ...  analysis of various page features [6] , and transductive link spam detection [18] .  ... 
doi:10.1145/1451983.1452000 dblp:conf/airweb/AndersenBCHJMT08 fatcat:poxyfn6xsnhgzpfefx52vprjey

Graphene-based biomimetic materials targeting urine metabolite as potential cancer biomarker: Application over different conductive materials for potentiometric transduction

Liliana A.A.N.A. Truta, Nádia S. Ferreira, M. Goreti F. Sales
2014 Electrochimica Acta  
Better slopes were achieved when the membrane was casted on conductive glass (−57.4mV/decade), while the best detection limits were obtained for graphite-based conductive supports (3.6×10 −5 mol/L).  ...  The SPAM material consisted of a 3D polymeric network created by surface imprinting on graphene layers.  ...  Werfen Group -Izasa Portugal and WITec GmbH is also acknowledged for the Raman Microscopy analysis of the SPAM materials.  ... 
doi:10.1016/j.electacta.2014.10.136 pmid:26456975 pmcid:PMC4597333 fatcat:ziu5crqalzfh5futon2uutcoya

Detecting Web Spam Based on Novel Features from Web Page Source Code

Jiayong Liu, Yu Su, Shun Lv, Cheng Huang, Liguo Zhang
2020 Security and Communication Networks  
Experiment results show that the proposed model could effectively detect web spam.  ...  Existing research mainly studies the content and links of websites. However, none of these techniques focused on semantic analysis of link and anchor text for detection.  ...  [27] addressed the web spam detection problem by using the graph neural network (GNN) architecture, which can act as a mixed transductive-inductive model that is able to classify pages by using both  ... 
doi:10.1155/2020/6662166 fatcat:opknwyq3jfe2baaa33xg4vhdli

Graph regularization methods for Web spam detection

Jacob Abernethy, Olivier Chapelle, Carlos Castillo
2010 Machine Learning  
We present an algorithm, WITCH, that learns to detect spam hosts or pages on the Web.  ...  The method is efficient, scalable, and provides state-of-the-art accuracy on a standard Web spam benchmark.  ...  link to non-spam hosts.  ... 
doi:10.1007/s10994-010-5171-1 fatcat:6o23qs5rpre3teiogmsha57omy

Adversarial Web Search

Carlos Castillo
2010 Foundations and Trends in Information Retrieval  
Section 4 describes link-based spam techniques and how to detect them, and covers topics such as link alliances and nepotistic linking.  ...  E-mail Spam Detection Content-based Web spam detection techniques overlap with the methods used for e-mail spam detection, to the extent that both Web spam and e-mail spam detection can be described as  ... 
doi:10.1561/1500000021 fatcat:toxnvajrmbdppf5hytdbnykuiq

ReP-ETD: A Repetitive Preprocessing technique for Embedded Text Detection from images in spam emails

Asha S Manek, D K Shamini, Veena H Bhat, P Deepa Shenoy, M. Chandra Mohan, K R Venugopal, L M Patnaik
2014 2014 IEEE International Advance Computing Conference (IACC)  
This work proposes new model ReP-ETD (Repetitive Pre-processing technique for Embedded Text Detection) for efficiently and accurately detecting spam in email images.  ...  Spammers are continuously adopting new techniques to evade detection.  ...  The proposed method employs a small amount of labeled data and extracts efficient image features to perform both transductive and inductive learning to detect the spam imageand achieves results of 88.40%  ... 
doi:10.1109/iadcc.2014.6779387 fatcat:fnkdyq6cire3dl6b75mfwrojeu

Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning

Ishan Durugkar, Elad Liebman, Peter Stone
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
It motivates some malicious merchants to promote their items by spam actions.  ...  ., 2017] focuses on graphbased fraud detection.  ... 
doi:10.24963/ijcai.2020/343 dblp:conf/ijcai/WangLHH0HC20 fatcat:pulsaiobfrhvbam3furaurciwy
« Previous Showing results 1 — 15 out of 395 results