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Deep Web

Deep Web
From Wikipedia, the free encyclopedia (Redirected from Deep Web) Deep Web may refer to: Related:  Online Search Tools - Deep Web Search

99 Resources to Research & Mine the Invisible Web College researchers often need more than Google and Wikipedia to get the job done. To find what you're looking for, it may be necessary to tap into the invisible web, the sites that don't get indexed by broad search engines. The following resources were designed to help you do just that, offering specialized search engines, directories, and more places to find the complex and obscure. Search Engines Whether you're looking for specific science research or business data, these search engines will point you in the right direction. Turbo10: On Turbo10, you'll be able to search more than 800 deep web search engines at a time. Databases Tap into these databases to access government information, business data, demographics, and beyond. GPOAccess: If you're looking for US government information, tap into this tool that searches multiple databases at a time. Catalogs If you're looking for something specific, but just don't know where to find it, these catalogs will offer some assistance. Directories

Web profond Un article de Wikipédia, l'encyclopédie libre. Ne doit pas être confondu avec darknet. Ne pas confondre[modifier | modifier le code] Ressources profondes[modifier | modifier le code] Les robots d'indexation sont des programmes utilisés par les moteurs de recherche pour parcourir le web. Afin de découvrir de nouvelles pages, ces robots suivent les hyperliens. On peut classer les ressources du web profond dans une ou plusieurs des catégories suivantes : contenu dynamique ;contenu non lié ;contenu à accès limité ;contenu de script ;format non indexable. Voir aussi la section raisons de la non-indexation qui donne plus de précision. Taille[modifier | modifier le code] Une étude de juillet 2001 réalisée par l'entreprise BrightPlanet[1] estime que le web profond pouvait contenir 500 fois plus de ressources que le web indexé par les moteurs de recherche. Web opaque[modifier | modifier le code] Une partie très importante du web est théoriquement indexable, mais non indexée de fait par les moteurs.

100 Useful Tips and Tools to Research the Deep Web By Alisa Miller Experts say that typical search engines like Yahoo! and Google only pick up about 1% of the information available on the Internet. The rest of that information is considered to be hidden in the deep web, also referred to as the invisible web. So how can you find all the rest of this information? This list offers 100 tips and tools to help you get the most out of your Internet searches. Meta-Search Engines Meta-search engines use the resources of many different search engines to gather the most results possible. SurfWax. Semantic Search Tools and Databases Semantic search tools depend on replicating the way the human brain thinks and categorizes information to ensure more relevant searches. Hakia. General Search Engines and Databases These databases and search engines for databases will provide information from places on the Internet most typical search engines cannot. DeepDyve. Academic Search Engines and Databases Google Scholar. Scientific Search Engines and Databases

Archimag Database search engine There are several categories of search engine software: Web search or full-text search (example: Lucene), database or structured data search (example: Dieselpoint), and mixed or enterprise search (example: Google Search Appliance). The largest web search engines such as Google and Yahoo! utilize tens or hundreds of thousands of computers to process billions of web pages and return results for thousands of searches per second. High volume of queries and text processing requires the software to run in highly distributed environment with high degree of redundancy. Modern search engines have the following main components: Searching for text-based content in databases or other structured data formats (XML, CSV, etc.) presents some special challenges and opportunities which a number of specialized search engines resolve. Database search engines were initially (and still usually are) included with major database software products. See also[edit] External links[edit]

Dark Internet Causes[edit] Failures within the allocation of Internet resources due to the Internet's chaotic tendencies of growth and decay are a leading cause of dark address formation. One form of dark address is military sites on the archaic MILNET. These government networks are sometimes as old as the original ARPANET, and have simply not been incorporated into the Internet's evolving architecture. See also[edit] References[edit]

List of academic databases and search engines This page contains a representative list of major databases and search engines useful in an academic setting for finding and accessing articles in academic journals, institutional repositories, archives, or other collections of scientific and other articles. As the distinction between a database and a search engine is unclear for these complex document retrieval systems, see: the general list of search engines for all-purpose search engines that can be used for academic purposesthe article about bibliographic databases for information about databases giving bibliographic information about finding books and journal articles. Note that "free" or "subscription" can refer both to the availability of the database or of the journal articles included. This has been indicated as precisely as possible in the lists below. See also[edit] References[edit] ^ "List of EBSCO databases".

Les 6 étapes d'un projet de recherche d'information (1996-2011) - Pédagogie du projet Démarche adaptée et mise à jour par Hélène Guertin avec la collaboration de Paulette Bernhard, professeure honoraire, École de bibliothéconomie et des sciences de l'information (EBSI), Université de Montréal, Québec, à partir de l'ouvrage La recherche d'information à l'école secondaire : l'enseignant et le bibliothécaire, partenaires de l'élève (1997) - Crédits Note : Le travail d'élaboration de la démarche a bénéficié de l'accès privilégié au document de travail daté de 1996, obtenu avec la permission de Yves Léveillé, dont le titre provisoire était La recherche d'information à l'école secondaire : un projet de recherche d'information en six étapes. La présente version remaniée (2005) respecte l'esprit du document : Les compétences transversales dans Programme de formation de l'école québécoise, enseignement secondaire (2004), ministère de l'Éducation du Québec. Autres modèles du processus de recherche d'information (site Form@net)

Business Solutions & Software for Legal, Education and Government | LexisNexis The University of South Carolina Beaufort So, you're still getting those 1,670,000+ responses to your search queries on the Web, and you're still too busy to do anything about it, like reading the lengthy, and sometimes confusing, "help" screens to find out how to improve your searching techniques. Look no further! Real help is here, in the USCB Library's BARE BONES Tutorial. You can zip through these lessons in no time, any time. They are very short and succinct; each can be read in a few minutes. Feel free to jump in wherever you like, skip what you don't want to read, and come back whenever you need to. The information contained in the following lessons is truly "bare bones," designed to get you started in the right direction with a minimum of time and effort. Lesson 1: Search Engines: a Definition Lesson 2: Metasearchers: a Definition Lesson 3: Subject Directories: a Definition Lesson 4: Library Gateways and Specialized Databases: a Definition Lesson 5: Evaluating Web Pages Lesson 6: Creating a Search Strategy Lesson 17: Yahoo!

ERIC – World’s largest digital library of education literature How to Properly Research Online (and Not Embarrass Yourself with the Results) Warning: if you are going to argue a point about politics, medicine, animal care, or gun control, then you better take the time to make your argument legit. Spending 10 seconds with Google and copy-pasting wikipedia links doesn't cut it. The standard for an intelligent argument is Legitimate research is called RE-search for a reason: patient repetition and careful filtering is what will win the day. There are over 86 billion web pages published, and most of those pages are not worth quoting. To successfully sift it all, you must use consistent and reliable filtering methods. If you are a student, or if you are seeking serious medical, professional, or historical information, definitely heed these 8 suggested steps to researching online:

The Invisible Web What is the Invisible Web? How can you find it online? What makes the Invisible Web search engines and Invisible Web databases so special? Find out the answers to these questions and learn more about this section of the Web that's so much larger than what you can uncover with an ordinary Web search. How to Mine the Invisible Web: The Ultimate GuideThe Invisible Web is a mammoth resource that is mostly untapped. Invisible Web People SearchThe Invisible Web is a goldmine of information, and since the Invisible Web is larger by far than the parts of the Web we can access with a simple search engine query, there's potentially much more information available. Five Search Engines You Can Use to Search the Invisible WebUnlike pages on the visible Web (that is, the Web that you can access from search engines and directories), information in the Invisible Web is just not visible to the software spiders and crawlers that create search engine indexes. The Invisible Web: How to Find It.

Web search query Types[edit] There are four broad categories that cover most web search queries:[1] Informational queries – Queries that cover a broad topic (e.g., colorado or trucks) for which there may be thousands of relevant results.Navigational queries – Queries that seek a single website or web page of a single entity (e.g., youtube or delta air lines).Transactional queries – Queries that reflect the intent of the user to perform a particular action, like purchasing a car or downloading a screen saver. Search engines often support a fourth type of query that is used far less frequently: Connectivity queries – Queries that report on the connectivity of the indexed web graph (e.g., Which links point to this URL? Characteristics[edit] A study of the same Excite query logs revealed that 19% of the queries contained a geographic term (e.g., place names, zip codes, geographic features, etc.).[4] Structured queries[edit] See also[edit] References[edit] Jump up ^ Christopher D.

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