By Haralambos Marmanis, Dmitry Babenko
Web 2.0 purposes offer a wealthy consumer adventure, however the components you can't see are only as important-and amazing. They use strong recommendations to approach info intelligently and supply beneficial properties in keeping with styles and relationships in info. Algorithms of the clever net indicates readers tips on how to use a similar strategies hired via loved ones names like Google advert experience, Netflix, and Amazon to remodel uncooked facts into actionable information.
Algorithms of the clever net is an example-driven blueprint for developing purposes that gather, learn, and act at the giant amounts of knowledge clients go away of their wake as they use the net. Readers learn how to construct Netflix-style advice engines, and the way to use an identical thoughts to social-networking websites. See how click-trace research may end up in smarter advert rotations. the entire examples are designed either to be reused and to demonstrate a normal process- an algorithm-that applies to a extensive variety of scenarios.
As they paintings during the book's many examples, readers know about advice structures, seek and score, computerized grouping of comparable items, type of gadgets, forecasting versions, and independent brokers. in addition they familiarize yourself with numerous open-source libraries and SDKs, and freely to be had APIs from the most popular websites on the net, equivalent to fb, Google, eBay, and Yahoo.
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Extra resources for Algorithms of the Intelligent Web
Typically, you either leave the missing values as missing or you fill them in with some default or calculated value. Both conditions can lead to unstable implementations. Your data may change. The database schema may change or the semantics of the data in the database may change. Your data may not be normalized. Let’s say that we’re looking at the weight of a set of individuals. In order to draw any meaningful conclusions based on the value of the weight, the unit of measurement should be the same for all individuals—in pounds or kilograms for every person, not a mix of measurements in pounds and kilograms.
The Lucene StandardTokenizer is a grammar-based tokenizer that’s constructed with JFlex, and it’s used in the StandardAnalyzer. To convince you of the analyzer’s importance, replace the StandardAnalyzer with the WhitespaceAnalyzer and observe the difference in the resulting scores. Lucene analyzers provide a wealth of capabilities, such as the ability to add synonyms, modify stop words (words that are explicitly removed from the text before indexing), and deal with non-English languages. We’ll use Lucene analyzers throughout the book, even in chapters that don’t deal with search.
It employs a syndication-specific language that’s expressed in plain XML format, without the need for XML namespaces or direct RDF referencing. 0 feeds today; these are typically free for individuals and nonprofit organizations for noncommercial use. com/rss) has plenty of resources for a smooth introduction in the subject. edu/rss. Finally, you can use Atom-based syndication. org/html/rfc4287). 0. It was in essence a compromise between the features of the existing standards under the constraint of maximum backward compatibility with the other syndication formats.
Algorithms of the Intelligent Web by Haralambos Marmanis, Dmitry Babenko