PUBLIC MARKS from camel with tags google & search

Wrapper is a cross-browser compliant HTML/CSS rendering engine written in ActionScript that sits on top of your standards compliant HTML page. Wrapper eliminates cross-browser issues and makes integrating ActionScript and HTML/CSS projects possible without needing to compile. Wrappers strives to answer the most common problems web designers face without forcing them to learn too many new things. Most web sites can be created in HTML or CSS, then when you need to extend Wrapper's capabilities you can either use JSON to call functions within ActionScript or you can load compiled plug-ins. Wrapper also has built in methods within CSS to load custom fonts, display elements as any shape, and fill them with linear or radial gradient background colors. ActionScript's event model is also implemented within Wrapper's HTML. Wrapper's best features are the ones that you get for free because of how it is set up. It's like getting all the great features of the Flash Player without needing to deal with compiling and being able to create your content the same way any HTML page would be created. Wrapper is fully accessible to the search engines and integrates well with any back-end technology. Wrapper is currently released as a fully functional open source beta for Flash Player 9. Wrapper is set up as a pre-compiled plug-in but can easily be integrated into any Flex or AIR applications or even as an ActionScript framework for creation of compiled projects.

J'ai pu rencontrer Ambroise à l'occasion des Search Engine Strategie de 2008. Nous avions alors discuté de divers sujets que vous devinerez aisément ;) Je lui avais également proposé une interview. Malheureusement cela n'était pas envisageable à l'époque.

Voici une liste non exhaustive des mots clefs reconnu par Google lors de recherche, ces mots clefs peuvent être précédé du signe moins ( - ) afin d'exclure des résultats des termes :

Every day, search companies like Google download terabytes of data from the Internet, store it on clusters of thousands of machines, and process it so that it can be easily searched. To make this possible, these companies need sophisticated distributed file system and parallel programing architectures. Have you ever heard of the Map/Reduce distributed parallel programing paradigm? If you are a computer scientist, you should have, because every time you submit a Google search, you are using Map/Reduce. Despite growing demand from companies like Google, Yahoo, and Microsoft, few computer science majors have even heard of Map/Reduce, let alone graduate well versed in its use. Unfortunately, several barriers exist to integrating Map/Reduce into computer science curricula. Obtaining a large cluster, configuring it, and installing complicated distributed file system and parallel programing software is difficult, time consuming, and expensive. In the past, Google's solution to this problem has been to ship entire clusters pre-configured with Map/Reduce software to select universities. In essence, Vdoop does same thing, with exactly the same software, except for our clusters are virtual, and hence free.

Google commercialise désormais sa solution de recherche pour entreprises en version française, avec des baisses de tarifs importantes à la clé.

Le célèbre moteur de recherche Google permet aux webmasters d'intégrer à leurs pages un formulaire de recherche, de limiter la recherche à leur site et de personnaliser la page de résultats. Et tout ça, gratuitement. Article pour une intégration intelligente.