Operation
Selection-based search systems create what is known as a semantic database of trained terms. They do not compile a physical database or catalogue of the web on the users' desktop computer. Instead, they take a user's selected keyword or keywords, pass it to several heterogeneous online cloud services, categorize the keyword(s), and then compile the results in a homogeneous manner based on a specific algorithm.
No two selection-based search systems are alike. Some simply provide a list of links in a context menu to other websites, such as the proposed Internet Explorer 8 Accelerators feature. Others only allow the user to search his desktop files such as Macintosh Spotlight, or to search a popular search engine such as Google or Yahoo!, while others only search lesser-known search engines, newsgroups, and more specialized databases. Selection-based search systems also differ in how the results are presented and the quality of semantic categorization which is used. Some will open links to content in a new browser window. Others return content in floating information boxes which can be sized, shared, docked, etc.
A key challenge for selection-based search is that a long or nested list of categories quickly becomes unwieldy for the user. Therefore, it is incumbent upon the selection-based search system to both categorize the user-selected text and to identify those online services which most naturally apply to the selected text. For example, when the user selects an address, the system needs to identify the address as most suitable for an online mapping service such as Google Maps. When the user selects a movie title, the system needs to identify the selection as suitable for a movie database such as Internet Movie Database. When the user selects the name of a company, the system needs to identify the concordant stock symbol and an appropriate financial database such as Yahoo! Finance.
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