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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
