Towards Web Spam Filtering With Neural-based Approaches

dc.creatorSilva R.M.
dc.creatorAlmeida T.A.
dc.creatorYamakami A.
dc.date2012
dc.date2015-06-26T20:29:37Z
dc.date2015-11-26T14:26:05Z
dc.date2015-06-26T20:29:37Z
dc.date2015-11-26T14:26:05Z
dc.date.accessioned2018-03-28T21:29:00Z
dc.date.available2018-03-28T21:29:00Z
dc.identifier9783642346538
dc.identifierLecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). Springer Verlag, v. 7637 LNAI, n. , p. 199 - 209, 2012.
dc.identifier3029743
dc.identifier10.1007/978-3-642-34654-5_21
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84906718052&partnerID=40&md5=53c990d4c929dabfe2cdf7ecdefa868f
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/97105
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/97105
dc.identifier2-s2.0-84906718052
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1245971
dc.descriptionThe steady growth and popularization of the Web increases the competition between the websites and creates opportunities for profit in several segments. Thus, there is a great interest in keeping the website in a good position in search results. The problem is that many websites use techniques to circumvent the search engines which deteriorates the search results and exposes users to dangerous content. Given this scenario, this paper presents a performance evaluation of different models of artificial neural networks to automatically classify web spam.We have conducted an empirical experiment using a well-known, large and public web spam database. The results indicate that the evaluated approaches outperform the state-of-the-art web spam filters. © Springer-Verlag Berlin Heidelberg 2012.
dc.description7637 LNAI
dc.description
dc.description199
dc.description209
dc.descriptionet al.,Sociedad Colombiana de Computacion (SCo2),Universidad de Caldas,Universidad Nacional de Colombia,Universidad Tecnologica de Bolivar en Cartagena,Universidad Tecnologica de PereiraPublisher: Springer Verlag
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dc.languageen
dc.publisherSpringer Verlag
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsfechado
dc.sourceScopus
dc.titleTowards Web Spam Filtering With Neural-based Approaches
dc.typeActas de congresos


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