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Like other Google products such as the Chrome browser, QSB is open-source software. However, just as with Chrome, Google distributes official builds with extra functionality. In the case of QSB, this includes plugin validation, auto-update, and Google-branded icons. Later it became a fully open source product, and just called Quick Search Box. [4]
One thing the most visited websites have in common is that they are dynamic websites.Their development typically involves server-side coding, client-side coding and database technology.
Scala runs on the Java platform (Java virtual machine) and is compatible with existing Java programs. [15] As Android applications are typically written in Java and translated from Java bytecode into Dalvik bytecode (which may be further translated to native machine code during installation) when packaged, Scala's Java compatibility makes it well-suited to Android development, the more so when ...
Google Wave, later known as Apache Wave, was a software framework for real-time collaborative online editing. Originally developed by Google and announced on May 28, 2009, [ 1 ] [ 2 ] [ 3 ] it was renamed to Apache Wave when the project was adopted by the Apache Software Foundation as an incubator project in 2010.
Google X – redesigned Google search homepage. It appeared in Google Labs, but disappeared the following day for undisclosed reasons. [120] Accessible Search – search engine for the visually impaired. Quick Search Box – search box, based on Quicksilver, easing access to installed applications and online searches.
Google Programmable Search Engine (formerly known as Google Custom Search and Google Co-op) is a platform provided by Google that allows web developers to feature specialized information in web searches, refine and categorize queries and create customized search engines, based on Google Search.
Chrome Web Store was publicly unveiled in December 2010, [2] and was opened on February 11, 2011, with the release of Google Chrome 9.0. [3] A year later it was redesigned to "catalyze a big increase in traffic, across downloads, users, and total number of apps". [4]
Implicit collaboration characterizes Collaborative filtering and recommendation systems in which the system infers similar information needs. I-Spy, [5] Jumper 2.0, Seeks, the Community Search Assistant, [6] the CSE of Burghardt et al., [7] and the works of Longo et al. [8] [9] [10] all represent examples of implicit collaboration. Systems that ...