Partial information basis for agent-based collaborative dialogue

Moubaiddin, Asma; Obeid, Nadim

doi:10.1007/s10489-007-0108-5

Cited by 24 publications

(4 citation statements)

References 33 publications

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“…A dialog is represented as a sequence of Information States [26,105]. Two different methodologies are described to select the next user action given a history of information states.…”

Section: Modeling the User Intentionmentioning

confidence: 99%

“…Conversational interfaces [86,94,105,113,118] have been proven useful for providing the general public with access to telemedicine services, promoting patients' involvement in their own care, assisting in health care delivery, and improving patient outcome [19]. Bickmore and Giorgino define these systems as being "those automated systems whose primary goal is to provide health communication with patients or consumers primarily using natural language dialog" [19].…”

Section: Introductionmentioning

confidence: 99%

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Modeling the user state for context-aware spoken interaction in ambient assisted living

2014

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Ambient Assisted Living (AAL) systems must provide adapted services easily accessible by a wide variety of users. This can only be possible if the communication between the user and the system is carried out through an interface that is simple, rapid, effective, and robust. Natural language interfaces such as dialog systems fulfil these requisites, as they are based on a spoken conversation that resembles human communication. In this paper, we enhance systems interacting in AAL domains by means of incorporating context-aware conversational agents that consider the external context of the interaction and predict the user's state. The user's state is built on the basis of their emotional state and intention, and it is recognized by means of a module conceived as an intermediate phase between natural language understanding and dialog management in the architecture of the conversational agent. This prediction, carried out for each user turn in the dialog, makes it possible to adapt the system dynamically to the user's needs. We have evaluated our proposal developing a context-aware system adapted to patients suffering from chronic pulmonary diseases, and provide a detailed discussion of the positive influenc of our proposal in the success of the interaction, the information and services provided, as well as the perceived quality.

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“…A dialog is represented as a sequence of Information States [26,105]. Two different methodologies are described to select the next user action given a history of information states.…”

Section: Modeling the User Intentionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling the user state for context-aware spoken interaction in ambient assisted living

2014

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“…Agents are specialized problem-solving entities that have well-defined boundaries and the ability to communicate with other agents. ey are designed to fulfill a specific purpose and exhibit flexible and proactive behaviors [11].…”

Section: Introductionmentioning

confidence: 99%

Multiagent System for Mutual Collaboration Classification for Cancer Detection

Qasem

Hudaib

Obeid

2019

Mathematical Problems in Engineering

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A multiagent system (MAS) is a mechanism for creating goal-oriented autonomous agents in shared environments with communication and coordination facilities. Distributed data mining benefits from this goal-oriented mechanism by implementing various distributed clustering, classification, and prediction techniques. Hence, this study developed a novel multiagent model for distributed classification tasks in cancer detection with the collaboration of several hospitals worldwide using different classifier algorithms. A hospital agent requests help from other agents for instances that are difficult to classify locally. The agents communicate their beliefs (calculated classification), and others decide on the benefit of using such beliefs in classifying instances and adjusting their prior assumptions on each class of data. A MAS model state and behavior and communication are then developed to facilitate information sharing among agents. Regarding accuracy, implementing the proposed approach in comparison with typically different noncommunicated distributed classifications shows that sharable information considerably increases the classification task accuracy by 25.77%.

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“…In order As the trend to an increasing number of ubiquitous, connected devices continues to grow, the heterogeneity of client capabilities and the number of methods for accessing information services also increases. Thus, effectively bringing information and services to people can only be done by supporting pervasive computing, in which technical details are transparent to the user and the access to services is guaran-to develop these interfaces, in the last years there has been an increasing interest in simulating human-to-human communication, employing spoken dialog systems [25,30,36,40]. A dialog system can be understood as an automatic system which functionality is accessible through natural language, emulating human conversation.…”

Section: Introductionmentioning

confidence: 99%

Bringing context-aware access to the web through spoken interaction

2012

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The web has become the largest repository of multimedia information and its convergence with telecommunications is now bringing the benefits of web technology to handheld devices. To optimize data access using these devices and provide services which meet the user needs through intelligent information retrieval, the system must sense and interpret the user environment and the communication context. In addition, natural spoken conversation with handheld devices makes possible the use of these applications in environments in which the use of GUI interfaces is not effective, provides a more natural human-computer interaction, and facilitates access to the web for people with visual or motor disabilities, allowing their integration and the elimination of barriers to Internet access. In this paper, we present an architecture for the design of context-aware systems that use speech to access web services. Our contribution focuses specifically on the use of context information to improve the effectiveness of providing web services by using a spoken dialog system for the user-system interaction. We also describe an application of our proposal to develop a context-aware railway information system, and provide a detailed evaluation of the influence of the context information in the quality of the services that are supplied.

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Partial information basis for agent-based collaborative dialogue

Cited by 24 publications

References 33 publications

Modeling the user state for context-aware spoken interaction in ambient assisted living

Modeling the user state for context-aware spoken interaction in ambient assisted living

Multiagent System for Mutual Collaboration Classification for Cancer Detection

Bringing context-aware access to the web through spoken interaction

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