Graph regularization methods for Web spam detection
نویسندگان
چکیده
منابع مشابه
islanding detection methods for microgrids
امروزه استفاده از منابع انرژی پراکنده کاربرد وسیعی یافته است . اگر چه این منابع بسیاری از مشکلات شبکه را حل می کنند اما زیاد شدن آنها مسائل فراوانی برای سیستم قدرت به همراه دارد . استفاده از میکروشبکه راه حلی است که علاوه بر استفاده از مزایای منابع انرژی پراکنده برخی از مشکلات ایجاد شده توسط آنها را نیز منتفی می کند . همچنین میکروشبکه ها کیفیت برق و قابلیت اطمینان تامین انرژی مشترکان را افزایش ...
15 صفحه اولApproaches for Web Spam Detection
Spam is a major threat to web security. The web of trust is being abused by the spammers through their ever evolving new tactics for their personal gains. In fact, there is a long chain of spammers who are running huge business campaigns under the web. Spam causes underutilization of search engine resources and creates dissatisfaction among web community. Web Security being a prime challenge fo...
متن کاملWeb Spam Detection
Definition Web spam refers to a host of techniques to subvert the ranking algorithms of web search engines and cause them to rank search results higher than they would otherwise. Examples of such techniques include content spam (populating web pages with popular and often highly monetizable search terms), link spam (creating links to a page in order to increase its linkbased score), and cloakin...
متن کاملA Survey on Web Spam Detection Methods: Taxonomy
Web spam refers to some techniques, which try to manipulate search engine ranking algorithms in order to raise web page position in search engine results. In the best case, spammers encourage viewers to visit their sites, and provide undeserved advertisement gains to the page owner. In the worst case, they use malicious contents in their pages and try to install malware on the victim’s machine....
متن کاملGraph Labelling Workshop and Web Spam Challenge
We compare a wide range of semi-supervised learning techniques both for Web spam filtering and for telephone user churn classification. Semisupervised learning has the assumption that the label of a node in a graph is similar to those of its neighbors. In this paper we measure this phenomenon both for Web spam and telco churn. We conclude that spam is often linked to spam while honest pages are...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2010
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-010-5171-1