User Modelling, Dialog Structure, and Dialog Strategy in HAM-ANS
41565Authors
nan
Abstract
AI dialog systems are now developing from question-answering systems toward advising systems. This includes: discussed here, but see (Jameson, Wahlster 1982). The second part of this paper presents user modelling with respect to a dialog strategy which selects and verbalizes the appropriate speech act of recommendation. - structuring dialog - understanding and generating a wider range of speech acts than simply information request and answer - user modelling User modelling in HAM-ANS is closely connected to dialog structure and dialog strategy. In advising the user, the system generates and verbalizes speech acts. The choice of the speech act is guided by the user profile and the dialog strategy of the system.
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USER MODELLING, DIALOG STRUCTURE, AND DIALOG STRATEGY IN RAM-ANS Katharina Morik Technische Universitaet Berlin Project group KIT , Sekr. FR 5-8 Franklinstr. 28/29 D-IO00 Berlin i0 (Fed. Rep. Germany) ABSTRACT AI dialog systems are now developing from question-answering systems toward advising systems. This includes: discussed here, but see (Jameson, Wahlster 1982). The second part of this paper presents user modelling with respect to a dialog strategy which selects and verbalizes the appropriate speech act of recommendation. - structuring dialog - understanding and generating a wider range of speech acts than simply information request and answer - user modelling User modelling in HAM-ANS is closely connected to dialog structure and dialog strategy. In advising the user, the system generates and verbalizes speech acts. The choice of the speech act is guided by the user profile and the dialog strategy of the system. INTRODUCTION The HAMburg Application-oriented Natural language System (HAM-ANS) which has been developed for 3 years is now accomplished. We could perform numerous dialogs with the system thus determining the advantages and shortcomings of our approach (Hoeppner at al. |984). So now the time has come to show the open problems and what we have learned as did the EUFID group when they accomplished their system (Templeton, Burger 1983). This paper does not evaluate the overall HAM-ANS but is restricted to the aspect of dialog structuring and user modelling. Dialog structure is represented at two levels: the outline of the dialog is explicitly represented by a top (evel routine, embedded sub-dialogs are a result of the processing strategy of HAM-ANS. The overall dialog structure is utilized for determining the appropriate degree of detail of the referential knowledge for a particular dialog phase. The embedded sub-dialogs refer to other knowledge sources than the referential knowledge. In the first part of this paper dialog structuring in HAM-ANS is described. Handling of dialog phenomena as ellipsis and anaphora is not DIALOG STRUCTURE In one of its three applications HAM-ANS plays the role of a hotel clerk who advises the user in selecting a suitable room. The task of advising can be seen here as a comparison of the demands made on an object by the client and the advisor's knowledge about available objects, performed in order to determine the suitability of an object for the client. Dialogs between hotel clerks at the reception and the becoming hotel guest are usually short and stereotyped but offer some flexibility as well because the ~ruests do not establish a homogeneous group. With recourse to this restricted dialog type we modelled the outline of the dialog. Dialog structure is not represented in terms of some actions the user might want to perform as did Grosz (1977), Allen (1979), Litman,Allen (1984) nor in terms of information goals of the user as did Pollack (1984), but we represent and use knowledge about a dialog type. For formal dialogs in a well defined comunication setting this is possible. For a practical application the dialog phases and steps should be empirically …
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AI dialog systems are now developing from question-answering systems toward advising systems. This includes: discussed here, but see (Jameson, Wahlster 1982). The second part of this paper presents user modelling with respect to a dialog strategy which selects and verbalizes the appropriate speech act of recommendation. - structuring dialog - understanding and generating a wider range of speech acts than simply information request and answer - user modelling User modelling in HAM-ANS is closely connected to dialog structure and dialog strategy. In advising the user, the system generates and verbalizes speech acts. The choice of the speech act is guided by the user profile and the dialog strategy of the system.
Publication Details
- Paper ID:
- 41565
- Year:
- 1985
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan