Intelligent query answering in deductive and object-oriented databases
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Logical foundations of object-oriented and frame-based languages
Journal of the ACM (JACM)
Intensional query answering by partial evaluation
Journal of Intelligent Information Systems
Machine Learning
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Intensional Answers to Database Queries
IEEE Transactions on Knowledge and Data Engineering
ILPS '97 International Seminar on Logic Databases and the Meaning of Change, Transactions and Change in Logic Databases
Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information
DS-8 Proceedings of the IFIP TC2/WG2.6 Eighth Working Conference on Database Semantics- Semantic Issues in Multimedia Systems
Advances in Open Domain Question Answering (Text, Speech and Language Technology)
Advances in Open Domain Question Answering (Text, Speech and Language Technology)
Towards portable natural language interfaces to knowledge bases - The case of the ORAKEL system
Data & Knowledge Engineering
Generating approximate geographic descriptions
Empirical methods in natural language generation
Hi-index | 0.00 |
We present an approach for computing intensional answers given a set of extensional answers returned as a result of a user query to an information system. Intensional answers are considered as descriptions of the actual answers in terms of properties they share and which can enhance a user's understanding of the answer itself but also of the underlying knowledge base. In our approach, an intensional answer is represented by a clause and computed based on Inductive Logic Programming (ILP) techniques, in particular bottom-up clause generalization. The approach is evaluated in terms of usefulness and time performance, and its potential for helping to detect flaws in the knowledge base is discussed. While the approach is used in the context of a natural language question answering system in our setting, it clearly has applications beyond.