User Models in Dialog Systems 1989
DOI: 10.1007/978-3-642-83230-7_5
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Detecting and Responding to Plan-Oriented Misconceptions

Abstract: This paper discusses the problem of recognizing and responding to plan-oriented misconceptions in advice-seeking dialogs, concentrating on the problems of novice computer users. A cooperative response is one that not only corrects the user's mistaken belief, but also addresses the missing or mistaken user beliefs that led to it. Responding appropriately to a potentially incorrect user belief is presented as a process of 1. checking whether the advisor holds the user's belief; 2. confirming the belief as a misc… Show more

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Cited by 26 publications
(14 citation statements)
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“…This approach has been strongly promoted in the domain of providing expert medical advice (Miller, 1984). However it is also central to several operating system help systems, including Wizard (Finin, 1983) and AQUA (Quilici et al, 1988). In such systems, a user's attempt at solving a simple problem (such as deleting a group of files) is observed, and a "better" approach is suggested by the system.…”
Section: Overview Of Plan Realization Issuesmentioning
confidence: 99%
“…This approach has been strongly promoted in the domain of providing expert medical advice (Miller, 1984). However it is also central to several operating system help systems, including Wizard (Finin, 1983) and AQUA (Quilici et al, 1988). In such systems, a user's attempt at solving a simple problem (such as deleting a group of files) is observed, and a "better" approach is suggested by the system.…”
Section: Overview Of Plan Realization Issuesmentioning
confidence: 99%
“…However, there have been some notable attempts to address the problem of recognition of faulty plans. Classifications of different types of plan-based misconceptions are presented in [Pollack 1986, Quilici et al 1988, van Beek et al 1993, with a comprehensive and detailed list provided in [Calistri-Yeh 1991]. The emphasis in that work is on identifying user misconceptions, with no consideration given to potential problems in the underlying domain knowledge.…”
Section: Ifmentioning
confidence: 99%
“…For example, by inferring an underlying plan motivating a user's utterances, a system can anticipate obstacles that might prevent the user from successfully executing his/her plan, and provide augmented responses to remove these obstacles . In addition to using plan recognition to supply more information than explicitly requested , plan recognition has formed the basis of systems that understand indirect speech acts ), respond to ill-formed queries (Carberry, 1988), detect and correct misconceptions (Quilici, 1989), handle queries based on invalid plans (Pollack, 1990), and recognize complex discourse acts such as expressions of doubt (Carberry and Lambert, 1999). Plan-based reasoning has also provided new methodologies for handling traditional linguistic phenomena, such as resolving referring expressions (Grosz, 1977) and inter-sentential ellipsis (Carberry, 1985;Litman, 1986).…”
Section: Natural Language Understanding^plan Recognitionmentioning
confidence: 99%