Observations based on user actions will be reported to BGP-MS by the hypertext system. The application can ask BGP-MS questions about the user and BGP-MS can in return report its current assumptions concerning the user.
KN-AHS draws assumptions about the userıs knowledge based on two information sources: namely an initial interview, and some of the hypertext actions which the user may perform. In the initial interview, questions are posed to the user that refer to his membership in clearly separable user subgroups (like 'computer science student'), and his exposure to PCs, hypertexts, etc. The user's replies become communicated to BGP-MS, which can activate initial stereotypes for the user. Certain actions that the user may perform at the interface of the hypertext system give rise to assumptions about his familiarity with individual concepts:
If the user requests an explanation, a graphic, an example or a glossary definition for a hotword, then he is assumed to be unfamiliar with this hotword. If the user unselects an explanation, a graphic, or an example for a hotword, then he is assumed to be familiar with this hotword. If the user requests additional details for a hotword, then he is assumed to be familiar with this hotword. With each hotword for which more information can be requested, a SB-ONE4 concept that represents this technical term in BGP-MS is associated. When KN-AHS draws an assumption about the user's familiarity with a hotword, KN-AHS notifies BGP-MS that the corresponding concept is known or unknown to the user. KN-AHS deals with stereotypes by using the stereotype managing mechanism of BGP-MS. This mechanism analyzes observations received from KN-AHS and checks the activation and retraction conditions of all stereotypes. It will then enter inheritance links between the individual user model and those stereotypes that become active, and delete links to stereotypes that become deactivated. In the current domain of KN-AHS, more than one stereotype can be active at the same time. Inferences within KN-AHS are based on the observed assumptions and technical domain knowledge represented in a SB-ONE concept hierarchy. When the user switches to a new text object, KN-AHS aims at adapting it to the user's presumed conceptual knowledge. For each hotword in the new text object, it asks BGP-MS about the user's familiarity with the corresponding SB-ONE concept. The hotword is then treated in the following way:
If the user is unfamiliar with the associated concept, an explanation gets automatically added to the hotword. Also, an icon that symbolizes an available graphic for the hotword is placed near the hotword. If the user is familiar with the hotword, more details are automatically added after the hotword. If no information is available from BGP-MS concerning the userıs familiarity with the hotword, then the hotword is not changed.
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