Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …

The rise in popularity of social networking sites such as Twitter and Facebook has been
paralleled by the rise of unwanted, disruptive entities on these networks-—including …

Clickbaits are articles with misleading titles, exaggerating the content on the landing page.
Their goal is to entice users to click on the title in order to monetize the landing page. The …

Web-based social systems enable new community-based opportunities for participants to
engage, share, and interact. This community value and related services like search and …

The explosive growth of cyber attacks today, such as malware, spam, and intrusions, has
caused severe consequences on society. Securing cyberspace has become a great concern …

This is a survey of the science and practice of web crawling. While at first glance web
crawling may appear to be merely an application of breadth-first-search, the truth is that …

Search engines became a de facto place to start information acquisition on the Web. Though
due to web spam phenomenon, search results are not always as good as desired …

Web spam can significantly deteriorate the quality of search engine results. Thus there is a
large incentive for commercial search engines to detect spam pages efficiently and …

Various Web spam features and machine learning structures were constantly proposed to
classify Web spam in recent years. The aim of this paper was to provide a comprehensive …

Traditionally most of the anomaly detection algorithms have been designed
for'static'datasets, in which all the observations are available at one time. In non-stationary …