document: Detecting semantic cloaking on the web By supplying different versions of a web page to search engines and to browsers , a content provider attempts to cloak the real content from the view of the search engine . Semantic cloaking refers to differences in meaning between pages which have the effect of deceiving search engine ranking algorithms . In this paper , we propose an automated two-step method to detect semantic cloaking pages based on different copies of the same page downloaded by a web crawler and a web browser . The first step is a filtering step , which generates a candidate list of semantic cloaking pages . In the second step , a classifier is used to detect semantic cloaking pages from the candidates generated by the filtering step . Experiments on manually labeled data sets show that we can generate a classifier with a precision of 93 % and a recall of 85 % . We apply our approach to links from the dmoz Open Directory Project and estimate that more than 50,000 of these pages employ semantic cloaking .
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