An Ontology-Based Conversation System for Knowledge Bases
| Autor: | Robert J. Moore, Vasilis Efthymiou, Abdul Quamar, Jeffrey Kreulen, Fatma Ozcan, Dorian B. Miller, Chuan Lei |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
Computer science media_common.quotation_subject Natural language understanding Space (commercial competition) Ontology (information science) computer.software_genre Domain (software engineering) World Wide Web Health care Ontology Domain knowledge Conversation business computer media_common |
| Zdroj: | SIGMOD Conference |
| DOI: | 10.1145/3318464.3386139 |
| Popis: | Domain-specific knowledge bases (KB), carefully curated from various data sources, provide an invaluable reference for professionals. Conversation systems make these KBs easily accessible to professionals and are gaining popularity due to recent advances in natural language understanding and AI. Despite the increasing use of various conversation systems in open-domain applications, the requirements of a domain-specific conversation system are quite different and challenging. In this paper, we propose an ontology-based conversation system for domain-specific KBs. In particular, we exploit the domain knowledge inherent in the domain ontology to identify user intents, and the corresponding entities to bootstrap the conversation space. We incorporate the feedback from domain experts to further refine these patterns, and use them to generate training samples for the conversation model, lifting the heavy burden from the conversation designers. We have incorporated our innovations into a conversation agent focused on healthcare as a feature of the IBM Micromedex product. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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