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Although not Web-based, we take tools like Google Desktop Search as an example of individual-oriented vertical search systems.
Last week Google moved its search systems to the Chinese island dependency of Hong Kong.
From our viewpoint, large collections of search queries, made suitably anonymous, are essential resources for developing better search systems.
They're the creators of new industries — chips, PCs, servers, Web sites and ad-fueled search systems — on which others build.
It was followed by other search systems, like Veronica, Gopher and Archie, which predated the search engines offered today by Google, Microsoft, Yahoo and other companies.
Microsoft endured plenty of ribbing as it spent years building and then scrapping search systems meant to help it compete against Google.
On the bright side, apart from whatever the project does for national security, its innovations could eventually improve civilian search systems, much as the Pentagon's Arpanet eventually became the civilian Internet.
So I find that is a step closer to understanding than the current search systems.
The objective is to refine the search systems based on relevance judgements provided by users.
Many of existing semantic search systems provide graph-based querying interfaces.
This makes it difficult to apply DB schemas into encrypted database search systems.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com