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Improving user experience with case-based reasoning systems using text mining and Web 2.0

机译:使用文本挖掘和Web 2.0的基于案例的推理系统改善用户体验

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摘要

Many CBR systems have been developed in the past. However, currently many CBR systems are facing a sustainability issue such as outdated cases and stagnant case growth. Some CBR systems have fallen into disuse due to the lack of new cases, case update, user participation and user engagement. To encourage the use of CBR systems and give users better experience, CBR system developers need to come up with new ways to add new features and values to the CBR systems. The author proposes a framework to use text mining and Web 2.0 technologies to improve and enhance CBR systems for providing better user experience. Two case studies were conducted to evaluate the usefulness of text mining techniques and Web 2.0 technologies for enhancing a large scale CBR system. The results suggest that text mining and Web 2.0 are promising ways to bring additional values to CBR and they should be incorporated into the CBR design and development process for the benefit of CBR users.
机译:过去已经开发了许多CBR系统。但是,当前许多CBR系统都面临可持续性问题,例如过时的案例和停滞的案例增长。由于缺乏新案例,案例更新,用户参与和用户参与,一些CBR系统已被废弃。为了鼓励使用CBR系统并为用户提供更好的体验,CBR系统开发人员需要想出新的方法为CBR系统添加新的功能和价值。作者提出了一个框架,该框架使用文本挖掘和Web 2.0技术来改进和增强CBR系统,以提供更好的用户体验。进行了两个案例研究,以评估文本挖掘技术和Web 2.0技术对于增强大型CBR系统的有用性。结果表明,文本挖掘和Web 2.0是为CBR带来更多价值的有前途的方法,应该将它们纳入CBR设计和开发过程中,以使CBR用户受益。

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