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Naver was founded in June 1999 [1] as the first South Korean portal website with a self-developed search engine. In August 2000, Naver launched its 'comprehensive search' service, which allows users to get a variety of results from a single search query on one page, organized by type, including blogs, websites, images, and web communities.
The mission of ERIC is to provide a comprehensive, easy-to-use, searchable, Internet-based bibliographic and full-text database of education research and information for educators, researchers, and the general public. Education research and information are essential to improving teaching, learning, and educational decision-making.
An image search engine is a search engine that is designed to find an image. The search can be based on keywords, a picture, or a web link to a picture. The results depend on the search criterion, such as metadata, distribution of color, shape, etc., and the search technique which the browser uses.
The Terrorist Identities Datamart Environment (TIDE) is the U.S. government's central database on known or suspected international terrorists, and contains highly classified information provided by members of the Intelligence Community such as CIA, DIA, FBI, NSA, and many others. As of February 2017, there are 1.6 million names in TIDE. [1]
Google Search, offered by Google, is the most widely used search engine on the World Wide Web as of 2023, with over eight billion searches a day. This page covers key events in the history of Google's search service.
The sortable table below contains the three sets of ISO 3166-1 country codes for each of its 249 countries, links to the ISO 3166-2 country subdivision codes, and the Internet country code top-level domains (ccTLD) which are based on the ISO 3166-1 alpha-2 standard with the few exceptions noted.
Faceted search augments lexical search with a faceted navigation system, allowing users to narrow results by applying filters based on a faceted classification of the items. [1] It is a parametric search technique. [ 2 ]
The algorithm described herein is a type of local random search, where every iteration is dependent on the prior iteration's candidate solution. There are alternative random search methods that sample from the entirety of the search space (for example pure random search or uniform global random search), but these are not described in this article.