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基于水平可视图多元联合模体熵的多维EEG情感脑电信号识别
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作者 杨小冬 马志怡 +3 位作者 任彦霖 陈梅辉 何爱军 王俊 《中国科学:信息科学》 CSCD 北大核心 2023年第12期2406-2422,共17页
目前,许多基于深度学习和神经网络的算法被应用于脑电(electroencephalogram, EEG)信号情感识别.然而,现有研究大多采用提取单维脑电信号特征的方法.随着多传感技术的更新,更具全面性和系统性的多维信号特征提取需求出现.本文尝试将复... 目前,许多基于深度学习和神经网络的算法被应用于脑电(electroencephalogram, EEG)信号情感识别.然而,现有研究大多采用提取单维脑电信号特征的方法.随着多传感技术的更新,更具全面性和系统性的多维信号特征提取需求出现.本文尝试将复杂网络研究应用到多维情感脑电识别中,提出一种基于水平可视图多元联合模体熵的情感识别算法,该方法可以有效避免人工选取特征对实验结果的影响,保持原始序列的非线性动力学特征.首先利用水平可视图算法将多维情感脑电信号分别转换为多路可视图网络,提取模体熵特征识别情感脑电研究中的关键频带和关键通道.在此基础上,将水平可视图网络两两联合,提取多元水平联合模体熵向量,作为输入参数对情感脑电信号进行识别.由于情感脑电序列长度会对识别效果产生影响,我们将脑电信号切割成大小不一的窗口,对比不同窗口大小对分类准确率的影响.实验结果表明,当切割窗口大小为10 s时,多元水平联合模体熵对情感脑电信号的识别效果最佳,对积极脑电/消极脑电、积极脑电/中性脑电、消极脑电/中性脑电的分类准确率分别达到95.07%, 97.73%, 90.26%,优于其他二维连接参数.同时,三分类的准确率为93.67%,本文算法无论在识别复杂度和准确率上,与已有算法相比均有较大提高. 展开更多
关键词 EEG 多路水平可视图 多元联合模体熵 情感识别 多维分析
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Enhanced Answer Selection in CQA Using Multi-Dimensional Features Combination 被引量:3
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作者 Hongjie Fan zhiyi ma +2 位作者 Hongqiang Li Dongsheng Wang Junfei Liu 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2019年第3期346-359,共14页
Community Question Answering(CQA) in web forums, as a classic forum for user communication,provides a large number of high-quality useful answers in comparison with traditional question answering.Development of method... Community Question Answering(CQA) in web forums, as a classic forum for user communication,provides a large number of high-quality useful answers in comparison with traditional question answering.Development of methods to get good, honest answers according to user questions is a challenging task in natural language processing. Many answers are not associated with the actual problem or shift the subjects,and this usually occurs in relatively long answers. In this paper, we enhance answer selection in CQA using multidimensional feature combination and similarity order. We make full use of the information in answers to questions to determine the similarity between questions and answers, and use the text-based description of the answer to determine whether it is a reasonable one. Our work includes two subtasks:(a) classifying answers as good, bad, or potentially associated with a question, and(b) answering YES/NO based on a list of all answers to a question. The experimental results show that our approach is significantly more efficient than the baseline model, and its overall ranking is relatively high in comparison with that of other models. 展开更多
关键词 COMMUNITY QUESTION answering information RETRIEVAL MULTI-DIMENSIONAL features extraction SIMILARITY computation
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An approach to improve the quality of object-oriented models from novice modelers through project practice 被引量:1
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作者 zhiyi ma 《Frontiers of Computer Science》 SCIE EI CSCD 2017年第3期485-498,共14页
The defects in object-oriented models will result in poor quality of applications based on the models, and thus it is necessary to know which defects often occur in practice, to what extent they occur, why they occur,... The defects in object-oriented models will result in poor quality of applications based on the models, and thus it is necessary to know which defects often occur in practice, to what extent they occur, why they occur, and how they can be prevented. To gain deeper insights into these problems, this paper discusses how to improve the quality of object- oriented models from novice modelers through project prac- tice. This paper summarizes a set of typical quality defect types from a large number of the defects, and confirms them through our project practice. Moreover, the paper analyzes the improvement of the quality of object-oriented models by quantifying the level of occurrence for the defect types in dif- ferent phases of the project practice, and presents preventive measures by analyzing the causes for the defects to occur in object-oriented models in the aspects of syntax, semantics, and pragmatics. 展开更多
关键词 quality defects object-oriented models quality analysis project practice
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Assessing the quality of metamodels
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作者 zhiyi ma Xiao HE Chao LIU 《Frontiers of Computer Science》 SCIE EI CSCD 2013年第4期558-570,共13页
The complexity and diversity of modern software demands a variety of metamodel-based modeling languages for software development. Existing languages change continuously, and new ones are constantly emerging. In this s... The complexity and diversity of modern software demands a variety of metamodel-based modeling languages for software development. Existing languages change continuously, and new ones are constantly emerging. In this situation, and especially for metamodel-based modeling languages, a quality assurance mechanism for metamodels is needed. This paper presents an approach to assessing the quality of metamodels. A quality model, which systematically characterizes and classifies quality attributes, and an operable measuring mechanism for effectively assessing the quality of metamodels based on the quality model, are pre- sented, using UML as the main example. 展开更多
关键词 quality assessment METAMODELS METRIC
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