National Academies chapter explaining deep-web content, discovery limits and information retrieval.
This arXiv paper by Dirk Lewandowski and Philipp Mayr provides a critical review of Bergman's 2001 study on the Deep Web. It introduces the concept of the Academic Invisible Web, defined as databases and collections relevant to academia but not searchable by general-purpose internet search engines, and reviews approaches for indexing it. The authors question Bergman's size estimate and suggest collaboration.
A library support page explaining the invisible web, also called the deep web or hidden web. It states that search engines cover about 16% of the internet and advises against relying on them alone, especially for academic information. It lists content search engines cannot find, such as dynamically changing content, password protected resources and sites requiring registration, and suggests web directories and asking a librarian.
An arXiv paper on digging deeper into hidden web databases limited by the top-k output constraint. It presents the GetNext meta-algorithm, which retrieves the next ranked tuple through a restrictive interface without prior knowledge of the ranking function, and algorithms that generate and execute multiple reformulated queries. Theoretical analysis and experiments over synthetic and real-world databases are reported.
An arXiv paper on discovering skylines over hidden web databases whose search interfaces enforce a top-k output constraint. It examines how search interface controls affect discovery cost and develops algorithms for one-ended range, free range and point predicates, combined for mixed interfaces. Experiments over real-world online and offline databases are reported.
DARPA Memex is a program seeking to develop next-generation search technologies for discovering, organizing and presenting domain-specific content. It aims to extend search beyond a centralized model to the deep web and nontraditional content. The program initially plans to address fighting human trafficking. It is specifically not interested in deanonymizing servers, attributing identity to IP addresses, or accessing non-public information.
Bloomberg Industry Group accepts confidential news tips through SecureDrop, described as a secure communication platform designed to protect anonymity. Bloomberg Industry Group controls the server, which stores submitted information in encrypted form. The page advises against using home, office or employer networks and devices, recommending public wifi and devices the source controls. Signal and postal mail are listed as alternative methods.
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This arXiv paper by Dirk Lewandowski and Philipp Mayr provides a critical review of Bergman's 2001 study on the Deep Web. It introduces the concept of the Academic Invisible Web, defined as databases and collections relevant to academia but not searchable by general-purpose internet search engines, and reviews approaches for indexing it. The authors question Bergman's size estimate and suggest collaboration.
A library support page explaining the invisible web, also called the deep web or hidden web. It states that search engines cover about 16% of the internet and advises against relying on them alone, especially for academic information. It lists content search engines cannot find, such as dynamically changing content, password protected resources and sites requiring registration, and suggests web directories and asking a librarian.
An arXiv paper on digging deeper into hidden web databases limited by the top-k output constraint. It presents the GetNext meta-algorithm, which retrieves the next ranked tuple through a restrictive interface without prior knowledge of the ranking function, and algorithms that generate and execute multiple reformulated queries. Theoretical analysis and experiments over synthetic and real-world databases are reported.
An arXiv paper on discovering skylines over hidden web databases whose search interfaces enforce a top-k output constraint. It examines how search interface controls affect discovery cost and develops algorithms for one-ended range, free range and point predicates, combined for mixed interfaces. Experiments over real-world online and offline databases are reported.
DARPA Memex is a program seeking to develop next-generation search technologies for discovering, organizing and presenting domain-specific content. It aims to extend search beyond a centralized model to the deep web and nontraditional content. The program initially plans to address fighting human trafficking. It is specifically not interested in deanonymizing servers, attributing identity to IP addresses, or accessing non-public information.
Bloomberg Industry Group accepts confidential news tips through SecureDrop, described as a secure communication platform designed to protect anonymity. Bloomberg Industry Group controls the server, which stores submitted information in encrypted form. The page advises against using home, office or employer networks and devices, recommending public wifi and devices the source controls. Signal and postal mail are listed as alternative methods.
