User Models for Information Systems: Prospects and Problems

Expert systems attempt to model multiple aspects of human-computer interaction, including the reasoning of the human expert, the knowledge base, and characteristics and goals of the user. This paper focuses on models of the human user that are held by the system and utilized in interaction, with particular attention to information retrieval applications. User models may be classified along several dimensions, including static vs. dynamic, stated vs. inferred, and short-term vs. longterm models. The choice of the type of model will depend on a number of factors, including frequency of use, the relationship between the user and the system, the scope of the system, and the diversity of the user population. User models are most effective for well-defined tasks, domains, and user characteristics and goals. These user-system aspects tend not to be well defined in most information retrieval applications.published or submitted for publicatio

Planbasierte graphische Hilfe in objektorientierten Benutzungsoberflächen

Wir stellen das System PLUS vor, ein planbasiertes graphisches Hilfesystem für Applikationen mit einer objektorientierten Benutzerschnittstelle. Es werden die Hilfekomponente InCome+, die Animationskomponente und der graphik-orientierte Planeditor PlanEdit+ beschrieben. PlanEdit+ ermöglicht den interaktiven Aufbau der hierarchischen Planbasis, die die Grundlage für den Planerkennungsprozeß bildet.Eine zentrale Komponente der graphischen Hilfe in unserem System stellt das Modul InCome+ dar, das den Interaktionskontext des Benutzers visualisiert und darüberhinaus weitere Features wie semantische Undo- und Redo-Möglichkeiten und einen kontext-sensitiven Tutor zur Verfügung stellt. Als wesentliche Erweiterung der graphischen Benutzerunterstützung wird innerhalb von PLUS die Präsentation animierter Hilfe integriert. Es werden Benutzeraktionen simuliert, indem eine Animation über die aktuelle Benutzerschnittstelle gelagert wird. Die Animationssequenz wird im Kontext der aktuell vom Benutzer verfolgten Aufgabe generiert

Integrated plan generation and recognition : a logic-based approach

The work we present in this paper is settled within the field of intelligent help systems. Intelligent help systems aim at supporting users of application systems by the achievements of qualified experts. In order to provide such qualified support our approach is based on the integration of plan generation and plan recognition components. Plan recognition in this context serves to identify the users goals and so forms the basis for an active user support. The planning component dynamically generates plans which are proposed for the user to reach her goal. We introduce a logic-based approach where plan generation and plan recognition is done on a common logical basis and both components work in some kind of cross-talk

Intelligent user support in graphical user interfaces

1. This paper presents a frontend to an intelligent help system based on plans called InCome (Interaction Control Manager). It visualizes user actions previously executed in a specific application as a graph structure and enables the user to navigate through this structure. A higher level of abstraction on performed user actions shows the dialog history, the interaction context and reachable goals. Finally, the user is able to act on the application via InCome by performing undo mechanisms as well as specifying user goals inferred already by the help system. 2. This paper describes the system PLUS, a plan-based help system for applications offering an object-oriented user interface. Our plan recognition process is based on a predefined static hierarchical plan base, that is modelled using a goal plan language. This language is designed to especially cope with the problems arising when plan recognition is performed in a graphical user interface environment whose interaction is based on a user-directed dialog by means of direct manipulation -- so-called Direct Manipulation User Interfaces. The plan hierarchy is entered using the interactive graphics-oriented plan editor PlanEdit+. The plan recognition module PlanRecognizer+ builds a dynamic plan base by mapping user actions to plans stored in the static plan base. The dynamic plan base contains hypotheses about tasks the user is pursuing at the moment. These plan hypotheses serve as a basis to offer various kinds of assistance to the user. A central component of our graphical help is the module InCome+. InCome+ visualizes user actions previously executed in an application as a graph structure and enables the user to navigate through this structure. A higher level of abstraction on performed actions shows the dialog history, the interaction context, and reachable goals. InCome+ offers special features like task-oriented undo und redo facilities and a context-sensitive tutor. As a substantial extension of the graphical user assistance, we integrate the presentation of animated help within PLUS. Animation sequences are generated in the context of the tasks the user is currently working on

THE LIVING CASE: SEARCHING FOR A DEEPER STRUCTURE IN THE CASE ANALYSIS PROCESS

One of the primary methods of instruction in business disciplines is the case. However, in its current form of written presentation, some of the basic learning goals associated with case instruction are compromised. We have used new forms of media involving computing and communication to build a novel learning environment, the Living Case, which flexibly and interactively presents cases along with provide dynamic, on-going feedback to students analyzing a case. In our research we have formalized the process of analyzing a case in order to recognize and interpret student analysis behavior so that provide relevant assistance can be provided. Case analysis is characterized as a problem solving activity driven by comprehension and reasoning operators. A search for these operators led us to build an inventory of reading activities. Twelve hours of protocols are analyzed using "retelling profiles" as an interpretation mechanism. Retelling profiles are visual time plots of the activities undertaken in a reading task. Our preliminary results suggest a deeper structure to case analysis which is common across business disciplines, cases, and individuals. Differences between the analysis strategies of experts and novices are also formalized. Finally, an expert's analogical reasoning strategy using task-specific knowledge encoded as "templates" is identified as a major contributor to their efficiency in solving cases. Templates of typical company situations and responses are triggered early in the analysis process, and subsequent data gathering and reasoning is directed by an attempt to apply the template to the case situation.Information Systems Working Papers Serie

Intelligent user support in graphical user interfaces

1. This paper presents a frontend to an intelligent help system based on plans called InCome (Interaction Control Manager). It visualizes user actions previously executed in a specific application as a graph structure and enables the user to navigate through this structure. A higher level of abstraction on performed user actions shows the dialog history, the interaction context and reachable goals. Finally, the user is able to act on the application via InCome by performing undo mechanisms as well as specifying user goals inferred already by the help system. 2. This paper describes the system PLUS, a plan-based help system for applications offering an object-oriented user interface. Our plan recognition process is based on a predefined static hierarchical plan base, that is modelled using a goal plan language. This language is designed to especially cope with the problems arising when plan recognition is performed in a graphical user interface environment whose interaction is based on a user-directed dialog by means of direct manipulation -- so-called Direct Manipulation User Interfaces. The plan hierarchy is entered using the interactive graphics-oriented plan editor PlanEdit+. The plan recognition module PlanRecognizer+ builds a dynamic plan base by mapping user actions to plans stored in the static plan base. The dynamic plan base contains hypotheses about tasks the user is pursuing at the moment. These plan hypotheses serve as a basis to offer various kinds of assistance to the user. A central component of our graphical help is the module InCome+. InCome+ visualizes user actions previously executed in an application as a graph structure and enables the user to navigate through this structure. A higher level of abstraction on performed actions shows the dialog history, the interaction context, and reachable goals. InCome+ offers special features like task-oriented undo und redo facilities and a context-sensitive tutor. As a substantial extension of the graphical user assistance, we integrate the presentation of animated help within PLUS. Animation sequences are generated in the context of the tasks the user is currently working on

THE LIVING CASE: SEARCHING FOR A DEEPER STRUCTURE IN THE CASE ANALYSIS PROCESS

One of the primary methods of instruction in business disciplines is the case. However, in its current form of written presentation, some of the basic learning goals associated with case instruction are compromised. We have used new forms of media involving computing and communication to build a novel learning environment, the Living Case, which flexibly and interactively presents cases along with provide dynamic, on-going feedback to students analyzing a case. In our research we have formalized the process of analyzing a case in order to recognize and interpret student analysis behavior so that provide relevant assistance can be provided. Case analysis is characterized as a problem solving activity driven by comprehension and reasoning operators. A search for these operators led us to build an inventory of reading activities. Twelve hours of protocols are analyzed using "retelling profiles" as an interpretation mechanism. Retelling profiles are visual time plots of the activities undertaken in a reading task. Our preliminary results suggest a deeper structure to case analysis which is common across business disciplines, cases, and individuals. Differences between the analysis strategies of experts and novices are also formalized. Finally, an expert's analogical reasoning strategy using task-specific knowledge encoded as "templates" is identified as a major contributor to their efficiency in solving cases. Templates of typical company situations and responses are triggered early in the analysis process, and subsequent data gathering and reasoning is directed by an attempt to apply the template to the case situation.Information Systems Working Papers Serie