Relevant bibliographies by topics / Webspam

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Webspam'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Webspam"

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Largillier, Thomas, and Sylvain Peyronnet. "Detecting Webspam Beneficiaries Using Information Collected by the Random Surfer." International Journal of Organizational and Collective Intelligence 2, no. 2 (2011): 36–48. http://dx.doi.org/10.4018/joci.2011040103.

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Search engines use several criteria to rank webpages and choose which pages to display when answering a request. Those criteria can be separated into two notions, relevance and popularity. The notion of popularity is calculated by the search engine and is related to links made to the webpage. Malicious webmasters want to artificially increase their popularity; the techniques they use are often referred to as Webspam. It can take many forms and is in constant evolution, but Webspam usually consists of building a specific dedicated structure of spam pages around a given target page. It is import
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Largillier, Thomas, and Sylvain Peyronnet. "Webspam demotion: Low complexity node aggregation methods." Neurocomputing 76, no. 1 (2012): 105–13. http://dx.doi.org/10.1016/j.neucom.2011.04.041.

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Manaskasemsak, Bundit, and Arnon Rungsawang. "Web spam detection using trust and distrust-based ant colony optimization learning." International Journal of Web Information Systems 11, no. 2 (2015): 142–61. http://dx.doi.org/10.1108/ijwis-12-2014-0047.

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Purpose – This paper aims to present a machine learning approach for solving the problem of Web spam detection. Based on an adoption of the ant colony optimization (ACO), three algorithms are proposed to construct rule-based classifiers to distinguish between non-spam and spam hosts. Moreover, the paper also proposes an adaptive learning technique to enhance the spam detection performance. Design/methodology/approach – The Trust-ACO algorithm is designed to let an ant start from a non-spam seed, and afterwards, decide to walk through paths in the host graph. Trails (i.e. trust paths) discovere
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Fdez-Glez, J., D. Ruano-Ordás, R. Laza, J. R. Méndez, R. Pavón, and F. Fdez-Riverola. "WSF2: A Novel Framework for Filtering Web Spam." Scientific Programming 2016 (2016): 1–18. http://dx.doi.org/10.1155/2016/6091385.

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Over the last years, research on web spam filtering has gained interest from both academia and industry. In this context, although there are a good number of successful antispam techniques available (i.e., content-based, link-based, and hiding), an adequate combination of different algorithms supported by an advanced web spam filtering platform would offer more promising results. To this end, we propose the WSF2 framework, a new platform particularly suitable for filtering spam content on web pages. Currently, our framework allows the easy combination of different filtering techniques includin
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Luckner, Marcin. "Practical Web Spam Lifelong Machine Learning System with Automatic Adjustment to Current Lifecycle Phase." Security and Communication Networks 2019 (February 20, 2019): 1–16. http://dx.doi.org/10.1155/2019/6587020.

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Machine learning techniques are a standard approach in spam detection. Their quality depends on the quality of the learning set, and when the set is out of date, the quality of classification falls rapidly. The most popular public web spam dataset that can be used to train a spam detector—WEBSPAM-UK2007—is over ten years old. Therefore, there is a place for a lifelong machine learning system that can replace the detectors based on a static learning set. In this paper, we propose a novel web spam recognition system. The system automatically rebuilds the learning set to avoid classification base
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Liu, Jiayong, Yu Su, Shun Lv, and Cheng Huang. "Detecting Web Spam Based on Novel Features from Web Page Source Code." Security and Communication Networks 2020 (December 17, 2020): 1–14. http://dx.doi.org/10.1155/2020/6662166.

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Search engine is critical in people’s daily life because it determines the information quality people obtain through searching. Fierce competition for the ranking in search engines is not conducive to both users and search engines. 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. In this paper, we propose a web spam detection method by extracting novel feature sets from the homepage source code and choosing the random forest (RF) as the classifier. The novel feature sets are
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Iqbal, Muhammad, Malik Muneeb Abid, Usman Waheed, and Syed Hasnain Alam Kazmi. "Classification of Malicious Web Pages through a J48 Decision Tree, a Naïve Bayes, a RBF Network and a Random Forest Classifier for WebSpam Detection." International Journal of u- and e- Service, Science and Technology 10, no. 4 (2017): 51–72. http://dx.doi.org/10.14257/ijunesst.2017.10.4.05.

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Haelterman, Jean-Claude. "Adjustable First Webspace Splint." Journal of Hand Therapy 9, no. 3 (1996): 249. http://dx.doi.org/10.1016/s0894-1130(96)80091-3.

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Collinson, Helen. "Webscan sets up ‘firewall’." Computers & Security 15, no. 2 (1996): 126. http://dx.doi.org/10.1016/0167-4048(96)89338-2.

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Burston, Jack. "Software Review: WebSwami Ver. 1.4." CALICO Journal 28, no. 1 (2010): 191–203. http://dx.doi.org/10.11139/cj.28.1.191-203.

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Dissertations / Theses on the topic "Webspam"

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Largillier, Thomas. "Probabilistic algorithms for large scale systems." Paris 11, 2010. http://www.theses.fr/2010PA112348.

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De nos jours, les systèmes informatiques ont une taille sans cesse croissante pour répondre aux besoins des utilisateurs. Que ce soit dans le domaine du calcul scientifique où de plus en plus d’ordinateurs sont reliés pour répondre à des problèmes sans cesse plus complexes ou dans le domaine du loisir avec un internet grandissant pour satisfaire toujours plus la curiosité des utilisateurs. Les défis qui concernent les réseaux à grande échelle sont nombreux : pouvoir garantir aux utilisateurs d’un cluster que leur calcul arrivera à terme et sans erreur dans un temps raisonnable, distribuer des
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Robles, Luna Esteban. "Agile managing of web requirements with WebSpec." Tesis, Universidad de Alicante, 2011. http://hdl.handle.net/10915/4197.

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Web application development is a complex and time consuming process that involves di erent stakeholders (ranging from customers to developers); these applications have some unique characteristics like navigational access to information, sophisticated interaction features, etc. However, there have been few proposals to represent those requirements that are speci c to Web applications. Consequently, validation of requirements (e.g. in acceptance tests) is usually informal, and as a result troublesome. To overcome these problems, this PhD Thesis proposes WebSpec, a domain speci c language for spe
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Jeong, Juyong. "WebSAT: Web-based systems administration tool." CSUSB ScholarWorks, 2005. https://scholarworks.lib.csusb.edu/etd-project/2667.

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Discusses the development of WebSAT (Web-based systems administration tool), a computer network tool that allows systems administrators to create and delete accounts, disable and enable existing accounts, manage disk space conveniently, monitor the status of all network printers, and monitor network security. The WebSAT application was implemented using PHP, a server-side embedded scripting language, with a MySQL database.
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McGoey, Jonathan P. "The nature of science portrayed in ecological webspace." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ39854.pdf.

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Alves, Stefan Eduard Raposo. "Towards improving WEBSOM with multi-word expressions." Master's thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/10169.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática<br>Large quantities of free-text documents are usually rich in information and covers several topics. However, since their dimension is very large, searching and filtering data is an exhaustive task. A large text collection covers a set of topics where each topic is affiliated to a group of documents. This thesis presents a method for building a document map about the core contents covered in the collection. WEBSOM is an approach that combines document encoding methods and Self-Organising Maps (SOM) to generate a document
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Klasson, Johannes, Jakub Binieda, Sebastian Sundin, et al. "Utveckling av Fashion Websom en flexibel slut-användaradministrerad plattform." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119672.

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Denna kandidatrapport redogör för arbetet med att utveckla en webbplats, med avsaknad avtidigare erfarenheter inom området. Arbetet var kopplat till en riktig kund med tanke att användaresultatet för försäljning av modeaccessoarer i verkligheten.I dokumentet beskrivs även de metoder som använts, och vilka resultat som dessa har lett till.Det innefattar också vilka erfarenheter som har förvärvats under projektets gång, och hur dessa kan utnyttjas i senare projekt.
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El, Jed Olfa. "WebSum : système de résumé automatique de réponses des moteurs de recherche." Toulouse 3, 2006. http://www.theses.fr/2006TOU30145.

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Cette thèse s’inscrit dans le cadre général de la recherche d’information et plus précisément, dans le cadre de la classification et l’organisation des documents Web. Notre objectif est de développer un système de résumé automatique des réponses d’un moteur de recherche dans un style encyclopédique (WebSum). Ce type de résumé vise à classer les réponses issues d’une recherche d’information à l’aide d’un moteur de recherche, selon les différents thèmes ou ce que nous appelons dans nos travaux, les facettes de la requête utilisateur. Pour réaliser cet objectif, nous proposons : Une méthode d’ide
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HSU, SHAO-HENG, and 徐紹恒. "Using Ensemble Learning and Cluster Analysis to Detect WebSpam." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/38200571963095648889.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>101<br>As internet grew rapidly, it carries an extensive range of information resources. However, the quality and reliability has become uneven. Therefore, most major search engines use their own ranking algorithms for users to find useful information more efficiently. However, spam websites take artificially improper manner to enhance their ranking in search engines in order to achieve advertising or the intent of misconduct. Such behavior will reduce the efficiency of search engines and may pose a threat to users. The main issue of detecting spam websites is the im
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Liao, Wan-Shu, and 廖婉淑. "Improving WEBSPAM Detection by Using a Hybrid Machine Learning." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/11457827614663420593.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>97<br>WEB Spamming is a kind of scheme to boost the ranking of a website on search engine deliberately higher than they deserve. We call those websites as “WEBSPAM”. Also, it is a crucial issue to detect those websites for many search engine providers, because this kind of websites will damage not only the performance but also the reputation of a search engine. Our research is aimed to improve the WEBSPAM detection by using a hybrid, supervised (SVM) and unsupervised (Cluster), machine learning. We evaluated our model on the well known WEBSPAM corpus, WEBSPAM UK2007,
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Santos, Eugénio Manuel Ferreira dos. "WebSAD." Master's thesis, 1999. http://hdl.handle.net/10400.26/36475.

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O descongelamento das carreiras na função pública e consequente crescimento do interesse dos órgãos executivos em gerir os seus trabalhadores de forma eficiente e eficaz, tem criado impacto na forma como os trabalhadores e membros do executivo olham para as ferramentas de gestão do sistema de avaliação. O Sistema Integrado de Avaliação de Desempenho da Administração Pública (SIADAP) é agora visto como uma forma de conseguir chegar ao interesse de todos, um sistema acessível, simples e que não represente mais um encargo ou esforço. O WebSAD é um projeto que pretende que a implementação do
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Books on the topic "Webspam"

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Wiederspan, Jon. Planning and managing Web sites on the Macintosh: The complete guide to WebSTAR and MacHTTP. Addison-Wesley Developers Press, 1996.

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Espaces 4e Student Edition + Supersite Plus + WebSAM. Vista Higher Learning, 2018.

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Sentieri, 3rd Edition, Supersite Plus, + WebSAM CODE ONLY. Vista Higher Learning, 2019.

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Tocaimaza-Hatch, C. Cecilia, and José A. Blanco;. Enlaces 2nd Looseleaf Textbook w/ SSPlus & WebSAM Code. VHL, 2017.

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Vistas, 6th edition Supersite Plus + WebSAM , CODE ONLY. Vista Higher Learning, 2020.

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Panorama 5th Ed Supersite, vText & WebSAM Code **CODE ONLY**. Vista Higher Learning, 2016.

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Vistas 5th Ed Looseleaf Textbook Vol 1 + SSPlus + WebSAM. 2016.

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Blanco, José A. Aventuras 5th Looseleaf Textbook w/ Supersite, vText & WebSAM Code. VHL, 2017.

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Protagonistas 2nd Student Edition w/ Supersite, vText & WebSAM Code. VHL, 2017.

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Blanco and VHL. Aventuras 5th Supersite, vText and WebSAM Code **CODE ONLY**. Vista Higher Learning, 2017.

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Book chapters on the topic "Webspam"

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Largillier, Thomas, and Sylvain Peyronnet. "Using Patterns in the Behavior of the Random Surfer to Detect Webspam Beneficiaries." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24396-7_19.

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Scott, Jeffrey. "Introduction to WebSim™." In Finding Alphas. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119057871.ch26.

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The WebSim Team. "Alphas and WebSim™ Fundamentals." In Finding Alphas. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119057871.ch27.

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The WebSim Team. "Understanding How WebSim™ Works." In Finding Alphas. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119057871.ch28.

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van Zwol, Roelof, and Peter M. G. Apers. "Retrieval Performance Experiment with the Webspace Method." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45495-0_18.

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Luna, Esteban Robles, Irene Garrigós, Julián Grigera, and Marco Winckler. "Capture and Evolution of Web Requirements Using WebSpec." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13911-6_12.

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Honkela, Timo, and Michael Knapek. "Interactive Two-Level WEBSOM for Organizational Exploration." In Artificial Neural Networks and Machine Learning – ICANN 2013. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40728-4_72.

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Qiang, Ma, Shinya Miyazaki, and Katsumi Tanaka. "WebSCAN: Discovering and Notifying Important Changes of Web Sites⋆." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44759-8_58.

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Mouček, Roman, and Pavel Mautner. "WEBSOM Method - Word Categories in Czech Written Documents." In Text, Speech and Dialogue. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04208-9_15.

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Cruz, Isabel F., Lijun Leo Liu, and Tony Y. Wu. "WebSA: Database Support for Efficient Web Site Navigation." In Advances in Visual Information Management. Springer US, 2000. http://dx.doi.org/10.1007/978-0-387-35504-7_24.

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Conference papers on the topic "Webspam"

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Largillier, Thomas, and Sylvain Peyronnet. "Lightweight Clustering Methods for Webspam Demotion." In 2010 IEEE/ACM International Conference on Web Intelligence-Intelligent Agent Technology (WI-IAT). IEEE, 2010. http://dx.doi.org/10.1109/wi-iat.2010.243.

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Iqbal, Muhammad, Malik Muneeb Abid, and Muqeet Ahmad. "Catching Webspam traffic with Artificial Immune System (AIS) classification algorithm." In 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS). IEEE, 2016. http://dx.doi.org/10.1109/icsess.2016.7883095.

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Parmar, Kumar, Anand Trivedi, Pratik Chauhan, and Krishna Suchak. "Webspam Detection Using Classification Algorithms and Optimizing the Performance of Classifiers by Selecting the Features." In 2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE). IEEE, 2020. http://dx.doi.org/10.1109/icstcee49637.2020.9277255.

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van Zwol, Roelof, and Peter M. G. Apers. "The webspace method." In the ninth international conference. ACM Press, 2000. http://dx.doi.org/10.1145/354756.354851.

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Hale, Scott A., Taha Yasseri, Josh Cowls, Eric T. Meyer, Ralph Schroeder, and Helen Margetts. "Mapping the UK webspace." In the 2014 ACM conference. ACM Press, 2014. http://dx.doi.org/10.1145/2615569.2615691.

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Kiss, Daniel, and Peter Baranyi. "3D webspace VS 2D website." In 2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom). IEEE, 2020. http://dx.doi.org/10.1109/coginfocom50765.2020.9237898.

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Hauglid, Jon O., Jon Heggland, and Roger Midstraum. "WebSTAR: video database on WWW." In Electronic Imaging, edited by Klara Nahrstedt and Wu-chi Feng. SPIE, 1999. http://dx.doi.org/10.1117/12.373531.

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Azcarraga, Arnulfo P., and Teddy N. Yap. "Extracting meaningful labels for WEBSOM text archives." In the tenth international conference. ACM Press, 2001. http://dx.doi.org/10.1145/502585.502593.

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Tee, Jason Yong-Jin, Lay-Ki Soon, and Choo-Yee Ting. "WebSum: Enhanced SumBasic algorithm for Web site summarization." In 2012 4th Conference on Data Mining and Optimization (DMO). IEEE, 2012. http://dx.doi.org/10.1109/dmo.2012.6329812.

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Liu, Chang, Jinyuan Jia, Qian Zhang, and Lei Zhao. "Lightweight WebSIM Rendering Framework Based on Cloud-Baking." In SIGSIM-PADS '17: SIGSIM Principles of Advanced Discrete Simulation. ACM, 2017. http://dx.doi.org/10.1145/3064911.3064933.

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Reports on the topic "Webspam"

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Wilk, Philip A. WebSPIT. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/785301.

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Karaul, Mehmet, Yannis A. Korilis, and Ariel Orda. WebSeAl: Web Server Allocation. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada439737.

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Furmanski, Wojtek. WebSpace - a WebWindows based gateway to the ANL LabSpace. Final report for period September 1, 1995 - August 31, 1998. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/799433.

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