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The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects. For example, in the ...
Most content based document retrieval systems use an inverted index algorithm. A signature file is a technique that creates a quick and dirty filter, for example a Bloom filter, that will keep all the documents that match to the query and hopefully a few ones that do not. The way this is done is by creating for each file a signature, typically ...
A database index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and storage space to maintain the index data structure. Indexes are used to quickly locate data without having to search every row in a database table every time said table is accessed.
Soundex is the most widely known of all phonetic algorithms (in part because it is a standard feature of popular database software such as IBM Db2, PostgreSQL, [2] MySQL, [3] SQLite, [4] Ingres, MS SQL Server, [5] Oracle, [6] ClickHouse, [7] Snowflake [8] and SAP ASE. [9]) Improvements to Soundex are the basis for many modern phonetic algorithms.
For example, if we had considered only r1 then we would have concluded that {A,B} is a candidate key, which is incorrect. However, we might be able to conclude from such a relation that a certain set is not a candidate key, because that set does not have the uniqueness property (example {A,D} for r1 ).
Access Database, used for addins (Access 2, 95, 97), previously used for workgroups (Access 2).mda Access Blank Database Template (2003 and earlier).mdn Access Access (SQL Server) detached database (2000).mdf Protected Access Database, with compiled VBA and macros (2003 and earlier).mde Access lock files (associated with .mdb).ldb
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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). Full-text-searching techniques appeared in the 1960s, for example IBM STAIRS from 1969, and became common in online bibliographic databases in the 1990s.