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• W2326804586 abstract "As deep web grows at a very fast pace, there has been increased interest in techniques that help efficiently locate deep-web interfaces. However, due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. We propose a two-stage framework, namely SmartCrawler, for efficient harvesting deep web interfaces. In the first stage, SmartCrawler performs site-based searching for center pages with the help of search engines, avoiding visiting a large number of pages. To achieve more accurate results for a focused crawl, SmartCrawler ranks websites to prioritize highly relevant ones for a given topic. In the second stage, SmartCrawler achieves fast in-site searching by excavating most relevant links with an adaptive link-ranking. To eliminate bias on visiting some highly relevant links in hidden web directories, we design a link tree data structure to achieve wider coverage for a website. Our experimental results on a set of representative domains show the agility and accuracy of our proposed crawler framework, which efficiently retrieves deep-web interfaces from large-scale sites and achieves higher harvest rates than other crawlers." @default.
• W2326804586 created "2016-06-24" @default.
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• W2326804586 date "2016-07-01" @default.
• W2326804586 modified "2023-09-30" @default.
• W2326804586 title "SmartCrawler: A Two-Stage Crawler for Efficiently Harvesting Deep-Web Interfaces" @default.
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• W2326804586 doi "https://doi.org/10.1109/tsc.2015.2414931" @default.
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