The uses of databases are manifold. They provide a means of retrieving records or parts of records and performing various calculations before displaying the results. The interface by which such manipulations are specified is called the query language. Whereas early query languages were originally so complex that interacting with electronic databases could be done only by specially trained individuals, modern interfaces are more user-friendly, allowing casual users to access database information.
The main types of popular query modes are the menu, the “fill-in-the-blank” technique, and the structured query. Particularly suited for novices, the menu requires a person to choose from several alternatives displayed on a monitor. The fill-in-the-blank technique is one in which the user is prompted to enter key words as search statements. The structured query approach is effective with relational databases. It has a formal, powerful syntax that is in fact a programming language, and it is able to accommodate logical operators. One implementation of this approach, the Structured Query Language (SQL), has the form
select [field Fa, Fb, . . ., Fn]
from [database Da, Db, . . ., Dn]
where [field Fa = abc] and [field Fb = def].
Structured query languages support database searching and other operations by using commands such as “find,” “delete,” “print,” “sum,” and so forth. The sentencelike structure of a SQL query resembles natural language except that its syntax is limited and fixed. Instead of using a SQL statement, it is possible to represent queries in tabular form. The technique, referred to as query-by-example (or QBE), displays an empty tabular form and expects the searcher to enter the search specifications into appropriate columns. The program then constructs a SQL-type query from the table and executes it.
The most flexible query language is of course natural language. The use of natural-language sentences in a constrained form to search databases is allowed by some commercial database management software. These programs parse the syntax of the query; recognize its action words and their synonyms; identify the names of files, records, and fields; and perform the logical operations required. Experimental systems that accept such natural-language queries in spoken voice have been developed; however, the ability to employ unrestricted natural language to query unstructured information will require further advances in machine understanding of natural language, particularly in techniques of representing the semantic and pragmatic context of ideas.