用户辅助代理间知识共享的社会-语境模型

B. Rajendran, K. Iyakutti
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引用次数: 2

摘要

用户辅助代理的目标是为用户的任务提供有效的帮助。当用户参与认知活动(如通过网络进行知识收集任务)时,当代理无法事先清楚地知道用户的任务时,问题变得具有挑战性。当代理本身不具备这些任务所需的知识时,挑战就会增加。正是在这种情况下,我们提出了一个在用户协助代理社区内的知识共享的社会上下文模型,该模型通过开放领域知识门户环境提供,供用户用于基于web的知识收集任务。通过实现社会上下文模型,智能体将自己参与到知识共享练习中,这可能允许每个智能体从其他智能体那里获得关于他们感兴趣的任务的知识,通过这些知识,他们可以帮助各自的用户。我们通过一个涉及来自不同领域的许多知识收集任务的实验来评估我们的模型,结果表明了该模型在代理、其任务和社区方面的有趣含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Socio-contextual model of knowledge sharing among user assisting agents
A goal of user assisting agents is to provide effective assistance to their users in their tasks. The problem becomes challenging when the users are involved in a cognitive activity such as a knowledge gathering task through the web, and when the agents cannot clearly know the task of their users in advance. The challenge grows when the agent themselves do not possess the knowledge required for such tasks. It is in this scenario that we propose a socio-contextual model of knowledge sharing within a community of user assisting agents, provided through the environment of an open domain knowledge portal, which are used by the users for their web based knowledge gathering tasks. The agents involve themselves in a knowledge sharing exercise by implementing the socio-contextual model that may allow each agent to gain knowledge about a task of their interest from other fellow agents through which they can assist their respective users. We evaluate our model through an experiment involving many knowledge gathering tasks from diverse domains and the results indicate interesting implications of the model with respect to the agents, their tasks and their community.
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