A search engine is an information retrieval system designed to help find information stored on a computer system. It is an information retrieval software program that discovers, crawls, transforms, and stores information for retrieval and presentation in response to user queries. The search results are usually presented in a list and are commonly called hits. A search engine normally consists of four components, as follows: a search interface, a crawler (also known as a spider or bot), an indexer, and a database. The crawler traverses a document collection, deconstructs document text, and assigns surrogates for storage in the search engine index. Online search engines store images, link data and metadata for the document as well.
The most public, visible form of a search engine is a Web search engine which searches for information on the World Wide Web.
Search engines provide an interface to a group of items that enables users to specify criteria about an item of interest and have the engine find the matching items. The criteria are referred to as a search query. In the case of text search engines, the search query is typically expressed as a set of words that identify the desired concept that one or more documents may contain. There are several styles of search query syntax that vary in strictness. It can also switch names within the search engines from previous sites. Whereas some text search engines require users to enter two or three words separated by white space, other search engines may enable users to specify entire documents, pictures, sounds, and various forms of natural language. Some search engines apply improvements to search queries to increase the likelihood of providing a quality set of items through a process known as query expansion. Query understanding methods can be used as standardized query language.
The list of items that meet the criteria specified by the query is typically sorted, or ranked. Ranking items by relevance (from highest to lowest) reduces the time required to find the desired information.
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Building on an ongoing case study of how readers navigate the corpus of BnF Gallica and on a nascent project at OpenEdition, I will venture an understanding of digital libraries as open spaces at the crossroads of political spaces—with their governance res ...
In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references). In a full-text search, a search engine examines all of the words in every stored document as it tries to match search criteria (for example, text specified by a user).
Multi-scale and multi-patch deep models have been shown effective in removing blurs of dynamic scenes. However, these methods still suffer from one major obstacle: manually designing a lightweight and high-efficiency network is challenging and time-consumi ...
IEEE2021
We present an extensive evaluation of a wide variety of promising design patterns for automated deep-learning (AutoDL) methods, organized according to the problem categories of the 2019 AutoDL challenges, which set the task of optimizing both model accura ...