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A methodology is presented for a prototype query processor that can infer the semantics of a query and thus allow a very natural-language-like request from a user. The inference is accomplished by fully inverting all attribute values, attribute names, and system keywords. All atoms of a query are treated in the same manner until the semantics are either positively inferred by the system or explicitly declared by the user. The implementation approach uses a common hash area containing: the attribute names, the inverted attribute values, the key words allowed by the query processor, and any synonyms that have been declared by the user. The methodology includes provision for performing updates, adds, and deletions as well as query. Advantages of the approach are the simplicity of the query language for the user and the elegance of the semantic interpretation by the system.

Query using inferential processing implemented with inverted hashed files