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Focused crawlers enable the automatic discovery of Web resources about a given topic by automatically navigatingthrough the Web link structure and selecting the hyperlinks to follow by estimating their relevance to the topic ofinterest. This work proposes a generic focused crawling framework for discovering resources on any given topicthat reside on the Surface or the Dark Web. The proposed crawler is able to seamlessly navigate through theSurface Web and several darknets present in the Dark Web (i.e., Tor, I2P, and Freenet) during a single crawl byautomatically adapting its crawling behavior and its classifier-guided hyperlink selection strategy based on thedestination network type and the strength of the local evidence present in the vicinity of a hyperlink. It investigates11 hyperlink selection methods, among which a novel strategy proposed based on the dynamic linear combinationof a link-based and a parent Web page classifier. This hybrid focused crawler is demonstrated for the discovery ofWeb resources containing recipes for producing homemade explosives. The evaluation experiments indicate theeffectiveness of the proposed focused crawler both for the Surface and the Dark Web

Hybrid focused crawling on the Surface and the Dark Web