An introduction to database systems: vol. I (4th ed.)
An introduction to database systems: vol. I (4th ed.)
Language features for flexible handling of exceptions in information systems
ACM Transactions on Database Systems (TODS)
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
Query generalization: a method for interpreting null answers
Proceedings from the first international workshop on Expert database systems
Database description with SDM: a semantic database model
ACM Transactions on Database Systems (TODS)
Developing a natural language interface to complex data
ACM Transactions on Database Systems (TODS)
The design and implementation of INGRES
ACM Transactions on Database Systems (TODS)
Logic and Databases: A Deductive Approach
ACM Computing Surveys (CSUR)
Principles of Database Systems
Principles of Database Systems
Understanding Natural Language
Understanding Natural Language
Cooperative Responses to Boolean Queries
Proceedings of the First International Conference on Data Engineering
Completeness Information and Its Application to Query Processing
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Cooperative responses from a portable natural language data base query system.
Cooperative responses from a portable natural language data base query system.
Generalization and memory in an integrated understanding system
Generalization and memory in an integrated understanding system
VAGUE: a user interface to relational databases that permits vague queries
ACM Transactions on Information Systems (TOIS)
The 3DIS: an extensible object-oriented information management environment
ACM Transactions on Information Systems (TOIS)
Integrity = validity + completeness
ACM Transactions on Database Systems (TODS)
FLEX: A Tolerant and Cooperative User Interface to Databases
IEEE Transactions on Knowledge and Data Engineering
Intensional Answers to Database Queries
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Machine learning for online query relaxation
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient detection of empty-result queries
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Empty versus overabundant answers to flexible relational queries
Fuzzy Sets and Systems
Online query relaxation via Bayesian causal structures discovery
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Incremental controlled relaxation of failing flexible queries
Journal of Intelligent Information Systems
Approximating query answering on RDF databases
World Wide Web
Modeling suppositions in users' arguments
UM'05 Proceedings of the 10th international conference on User Modeling
Relaxation paradigm in a flexible querying context
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
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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.