NDLI: A Reference of Intentions for Better Medical Communication

Content Provider	IEEE Xplore Digital Library
Author	Matsumoto, N. Tokosumi, A.
Copyright Year	2007
Description	Author affiliation: Tokyo Inst. of Technol., Tokyo (Matsumoto, N.; Tokosumi, A.)
Abstract	Within the medical settings, multiple intelligent agents (including doctors, nurses, patients, and various medical information systems) exist that differ in terms of backgrounds, knowledge bases, and their usage of terminology. In order to support safe and effective medical communication between these multiple intelligent agents, this paper reviews and discusses some ontological studies of verbal communication. In medical settings, breakdowns in verbal communication can sometimes occur between the parties involved. Two important conditions for successful verbal communication are (a) recognizing the speaker's intention and (b) understanding the contents of their verbal message. To realize better medical communication, it is essential to respond appropriately to both intentions and content. Recently, there has been an emergence of ontological research seeking to systematize knowledge to the aim of effective information exchange on the World Wide Web. We survey recent trends in ontological studies of verbal communication related to intentions and discuss some contributions for safer medical communication. This paper also introduces our intention reference system that is based on cognitive analysis of performative verbs, which convey utterance intentions. This system illustrates the differences in nuance between intentions such as [tanomu (ask for)] and [youkyuu-suru (request)], which could contribute in reducing communication errors.
Starting Page	453
Ending Page	456
File Size	4009310
Page Count	4
File Format	PDF
ISBN	9781424410774
DOI	10.1109/ICCME.2007.4381775
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	better communication Face recognition Ontologies Medical information systems Information retrieval Knowledge management Data mining Intelligent agent reference system Text recognition speaker intention Natural language processing Performance analysis ontology conversation
Content Type	Text
Resource Type	Article

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