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This stage refines the results to meet the query's exact specifications, ensuring high precision and relevance. This dual-stage processing is fundamental in environments with large, complex data sets where performance and accuracy are critical, such as in online transaction processing systems and large-scale analytical queries.
The purpose of query optimization, which is an automated process, is to find the way to process a given query in minimum time. The large possible variance in time justifies performing query optimization, though finding the exact optimal query plan, among all possibilities, is typically very complex, time-consuming by itself, may be too costly ...
The information need can be specified in the form of a search query. In the case of document retrieval, queries can be based on full-text or other content-based indexing. Information retrieval is the science [ 1 ] of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes ...
Evaluation measures for an information retrieval (IR) system assess how well an index, search engine, or database returns results from a collection of resources that satisfy a user's query. They are therefore fundamental to the success of information systems and digital platforms.
Query rewriting is a typically automatic transformation that takes a set of database tables, views, and/or queries, usually indices, often gathered data and query statistics, and other metadata, and yields a set of different queries, which produce the same results but execute with better performance (for example, faster, or with lower memory use). [1]
In other databases, alternatives to express the same query (other queries that return the same results) can be tried. Some query tools can generate embedded hints in the query, for use by the optimizer. Some databases - like Oracle - provide a plan table for query tuning. This plan table will return the cost and time for executing a query.
The algorithm relies on a join tree of the query, which is guaranteed to exist and can be computed in linear time for any acyclic query. The join tree is a tree structure that contains the query atoms as nodes and has the connectedness (or running intersection) property which states that for every query variable, the tree nodes that contain that variable form a connected subgraph.
Machine learning based query term weight and synonym analyzer for query expansion. LucQE - open-source, Java. Provides a framework along with several implementations that allow to perform query expansion with the use of Apache Lucene. Xapian is an open-source search library which includes support for query expansion; ReQue open-source, Python ...