Communicating with databases in natural language
Communicating with databases in natural language
The answerability of database queries
Information Systems
TEAM: an experiment in the design of transportable natural-language interfaces
Artificial Intelligence
A priori analysis of natural language queries
Information Processing and Management: an International Journal
Federated database systems for managing distributed, heterogeneous, and autonomous databases
ACM Computing Surveys (CSUR) - Special issue on heterogeneous databases
European Journal of Information Systems
An English language question answering system for a large relational database
Communications of the ACM
Information retrieval using a transportable natural language interface
SIGIR '83 Proceedings of the 6th annual international ACM SIGIR conference on Research and development in information retrieval
An efficient easily adaptable system for interpreting natural language queries
Computational Linguistics
Using narratives to convey knowledge in decision making support systems
Decision making support systems
Crafting Rules: Context-Reflective Data Quality Problem Solving
Journal of Management Information Systems
Discovering Cues to Error Detection in Speech Recognition Output: A User-Centered Approach
Journal of Management Information Systems
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A model is proposed that defines "context" for natural language queries in a multiple database environment and a suggested implementation for this model is described. The approach developed in this study relaxes the assumption usually made for natural language query systems that the context, in the form of a specific database, is given. The formal model defines a universe of discourse consisting of multiple contexts, each of which is represented by a database, which consists of a dictionary, a thesaurus, relations, columns, and values. A mechanism for identifying and selecting the appropriate context for a query and its implementation as a prototype are described. The integration of this mechanism into the general model of natural language query processing is indicated and implementational issues are discussed.