The ROMPER System: Responding to Object-Related Misconceptions using Perspective

The ROMPER System: Responding to Object-Related Misconceptions using Perspective 1 Kathleen F. McCoy Dept. of Computer and Information Sciences University of Delaware Newark, De. 19716 Abstract I As a user interacts with a database or expert system, s/he may reveal a misconception about the objects modeled by the system. This paper discusses the ROMPER system for responding to such misconceptions in a domain independent and context sensitive fashion. ROMPER reasons about possible sources of the misconception. It operates on a model of the user and generates a cooperative response based on this reasoning. The process is made context sensitive by augmenting the user model with a new notion of object perspective which highlights certain aspects of the user model due to previous discourse. 1 Introduction A study of transcripts of expert-user dialogues reveals that users often exhibit misconceptions about the objects mod- eled in a domain. This paper describes the ROMPER system (Responding to Object-Related Misconceptions using PERspec- tive) which is able to respond to certain classes of these mis- conceptions in a principled manner. In doing so the system sheds light not only on the process of correcting misconcep- tions, but also on issues in natural-language generation, user models, and modeling certain contextual effects by a "filtering" of the knowledge representation. The ROMPER system functions as a part of a natural- language interface to a database or expert system. Input to ROMPER is a specification that a misconception has been de- tected. In this work a miscwnception is defined to be some discrepancy between what the system believes (i.e., what is con- tained in the system knowledge base) and what the user believes (as exhibited through the conversation). The system knowledge base includes an object taxonomy and knowledge about object attributes and their possible values. Several factors may influence the structure and content of responses to queries that reveal misconceptions. These in- dude the goals of the conversstional participants. If the mis- conception is not important to these goals, the response may not address the misconception or may address it only mini- maliy. ROMPER is concerned with correcting misconceptions that are important to the current goals of the conversational participants and is thus concerned with generating a maximal IMuch of this work wu done while the author wM at the University of Pennsylvania and was partially supported by the ARO grant DAA20-84- K-0061 and the NFS grant MCS81-07290. response. This response is aimed at eliminating the discrepancy between what the user believes and what the system believes by bringing the user's knowledge into line with the system's. This means that the system must not only give the user the correct information, but must present it in such a way so as to have the user adopt that information. ROMPER has a user model available to aid in this task. The user model constitutes what the system believes the user believes about the domain. It contains the same kind of information as is contained in the sys- tem's knowledge base …

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