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In the context of search engines, query expansion involves evaluating a user's input (what words were typed into the search query area, and sometimes other types of data) and expanding the search query to match additional documents. Query expansion involves techniques such as: Finding synonyms of words, and searching for the synonyms as well
Query, a precise request for information retrieval made to a database, data structure or information system Query language, a computer language used to make queries into databases and information systems; Query string, in the World Wide Web, is an optional part of a URL; Web search query, a query entered by users into web search engines
A faceted query is a conjunction of such facets; e.g. a query such as (electronic OR computerized OR DRE) AND (voting OR elections OR election OR balloting OR electoral) is likely to find documents about electronic voting even if they omit one of the words "electronic" or "voting", or even both.
Query segmentation is a key component of query understanding, aiming to divide a query into meaningful segments. Traditional approaches, such as the bag-of-words model, treat individual words as independent units, which can limit interpretative accuracy. For languages like Chinese, where words are not separated by spaces, segmentation is ...
A concept search (or conceptual search) is an automated information retrieval method that is used to search electronically stored unstructured text (for example, digital archives, email, scientific literature, etc.) for information that is conceptually similar to the information provided in a search query.
Search query may refer to: Database query; Web search query; See also. Search engine (computing) This page was last edited on 29 ...
Proximity searching can be used with other search syntax and/or controls to allow more articulate search queries. Sometimes query operators like NEAR, NOT NEAR, FOLLOWED BY, NOT FOLLOWED BY, SENTENCE or FAR are used to indicate a proximity-search limit between specified keywords: for example, "brick NEAR house".
In the KDDCUP 2005 dataset, a majority of queries contain more than one meaning. Therefore, only using the keywords of the query to set up a vector space model for classification is not appropriate. Query-enrichment based methods [1] [2] start by enriching user queries to a collection of text documents through search engines. Thus, each query ...