分析人工智能聊天机器人ALICE(Artificial Linguistic Internet Computer Entity)的知识组织结构和内部推理机制,指出ALICE系统在语义推理方面的缺陷,提出使用语义网本体理论与ALICE推理机制相结合的解决方案,设计并实现了一个基于ALIC...分析人工智能聊天机器人ALICE(Artificial Linguistic Internet Computer Entity)的知识组织结构和内部推理机制,指出ALICE系统在语义推理方面的缺陷,提出使用语义网本体理论与ALICE推理机制相结合的解决方案,设计并实现了一个基于ALICE系统的语义推理接口。实验证明,该接口能够很好地支持基于自然语言的语义推理,且具有很高的满意率。展开更多
In this paper, we give a definition of the alternating iterative maximum likelihood estimator （AIMLE） which is a biased estimator. Furthermore we adjust the AIMLE to result in asymptotically unbiased and consistent ...In this paper, we give a definition of the alternating iterative maximum likelihood estimator （AIMLE） which is a biased estimator. Furthermore we adjust the AIMLE to result in asymptotically unbiased and consistent estimators by using a bootstrap iterative bias correction method as in Kuk （1995）. Two examples and simulation results reported illustrate the performance of the bias correction for AIMLE.展开更多
文摘分析人工智能聊天机器人ALICE(Artificial Linguistic Internet Computer Entity)的知识组织结构和内部推理机制,指出ALICE系统在语义推理方面的缺陷,提出使用语义网本体理论与ALICE推理机制相结合的解决方案,设计并实现了一个基于ALICE系统的语义推理接口。实验证明,该接口能够很好地支持基于自然语言的语义推理,且具有很高的满意率。
基金Supported by the National Natural Science Foundation of China(Grant Nos.7117103571173029+3 种基金1093100211071035)the Program for New Century Excellent Talents(Grant No.NCET-10-315)Excellent TalentsProgram of Liaoning Educational Committee(Grant No.2008RC15)
文摘In this paper, we give a definition of the alternating iterative maximum likelihood estimator （AIMLE） which is a biased estimator. Furthermore we adjust the AIMLE to result in asymptotically unbiased and consistent estimators by using a bootstrap iterative bias correction method as in Kuk （1995）. Two examples and simulation results reported illustrate the performance of the bias correction for AIMLE.
