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Common Crawl produces and maintains a repository of web crawl data that is openly accessible to everyone. The crawl currently covers 6 billion pages and the repository includes valuable metadata. The crawl data is stored on Amazon’s Public Data Sets , allowing it to be bulk downloaded as well as directly accessed for map-reduce processing in EC2. This makes wholesale extraction, transformation, and analysis of web data cheap and easy. Small startups or even individuals can now access high quality crawl data that was previously only available to large search engine corporations. For more information, please see the following pages: Processing Pipeline and Accessing the Data .
Common Crawl aims to change the big data game with our repository of over 40 terabytes of high-quality web crawl information into the Amazon cloud, the net total of 5 billion crawled pages. In this blog post, we’ll show you how you can harness the power of MapReduce data analysis against the Common Crawl dataset with nothing more than five minutes of your time, a bit of local configuration, and 25 cents. When Google unveiled its MapReduce algorithm to the world in an academic paper in 2004, it shook the very foundations of data analysis.
If you are a programmer /developer who often shuffles between writing code in multiple languages, check this search engine for all programming related documentation. If you are a programmer or a web developer who often needs to shuffle between writing code in multiple languages, check out searchco.de – this is an instant search engine for all programming related documentation and nothing else. You type a function name and searchco.de will pull a list of all languages where that function is available along with the syntax and description. Alternately, you may prefix the function name with the language name – like php delete – to limit your search results to a particular language. In addition to regular programming languages, searchco.de also indexes documentation for Windows and Linux commands.
As a new hire at Oneupweb , I recently relocated to the beautiful Traverse City area. As a result I have spent a lot of time lately browsing real estate listings online. The amount of data available through the Multiple Listing Service (MLS) and its many outlets can be overwhelming. Searching through it all can also be addicting and time consuming. Many times I’ve found myself browsing photos of houses late into the night. Fortunately, there are a lot of great tools available to filter all this data and help make your real estate search successful.
But there are other ways to search the web, using what are known as semantic search engines. Using a semantic search engine will ensure more relevant results based on the ability to understand the definition of the word or term that is being searched for, rather than on numbers. Semantic search engines are able to understand the context in which the words are being used, resulting in smart, relevant results.
The American embassy in London's Grosvenor Square is part of the Sipdis intelligence network. Photograph: Rex Features How did such an enormous electronic database come into existence and then apparently be so easily leaked? The answer lies in the tag "Sipdis" which appears on the string of address codes heading each cable.