A prototype electronic encyclopedia
ACM Transactions on Information Systems (TOIS)
Detecting patterns in a Lexical Data Base
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
An attempt to computerized dictionary data bases
COLING '80 Proceedings of the 8th conference on Computational linguistics
On the application of syntactic methodologies in automatic text analysis
SIGIR '89 Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval
A tool for the automatic creation, extension and updating of lexical knowledge bases
EACL '87 Proceedings of the third conference on European chapter of the Association for Computational Linguistics
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This paper describes a model for a lexical knowledge base (LKB). An LKB is a knowledge base management system (KBMS) which stores various kinds of dictionary knowledge in a uniform framework and provides multiple viewpoints to the stored knowledge.KBMSs for natural language knowledge will be fundamental components of knowledgeable environments where non-computer professionals can use various kinds of support tools for document preparation or translation. However, basic models for such KBMSs have not been established yet. Thus, we propose a model for an LKB focusing on dictionary knowledge such as that obtained from machine-readable dictionaries.When an LKB is given a key from a user, it accesses the stored knowledge associated with that key. In addition to conventional direct retrieval, the LKB has a more intelligent access capability to retrieve related knowledge through relationships among knowledge units. To represent complex and irregular relationships, we employ the notion of implicit relationships. In contrast to conventional database models where relationships between data items are statically defined at data generation time, the LKB extracts relationships dynamically by interpreting the contents of stored knowledge at run time. This makes the LKB more flexible; users can add new functions or new knowledge incrementally at any time. The LKB also has the capability to define and construct new virtual dictionaries from existing dictionaries. Thus users can define their own customized dictionaries suitable for their specific purposes.The proposed model provides a logical foundation for building flexible and intelligent LKBs.