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ABSTRACT
Every information system incorporates a database component, and a frequent activity of users of information systems is to present it with queries. These queries reflect the presuppositions of their authors about the system and the information it contains. With most query processors, queries that are based on erroneous presuppositions often result in null answers. These fake nulls are misleading, since they do not point out the user's erroneous presuppositions (and can even be interpreted as their affirmation). This article describes the SEAVE mechanism for extracting presuppositions from queries and verifying their correctness. The verification is done against three repositories of information: the actual data, their integrity constraints, and their completeness assertions. Consequently, queries that reflect erroneous presuppositions are answered with informative messages instead of null answers, and user-system communication is thus improved (an aspect that is particularly important in systems that often are accessed by naive users). First, the principles of SEAVE are described abstractly. Then, specific algorithms for implementing it with relational databases are presented, including a new method for storing knowledge and an efficient algorithm for processing queries against the knowledge.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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REVIEW
"Forouzan Golshani : Reviewer"
Often users of database systems submit queries reflecting certain
assumptions that they have made about the information contained in the system.
For example, a user may ask the question: “Is Jack's brother older than 25
years?” The q
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