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< Page ,Total 23 >
Identifying suspicious groups of affiliated-transaction-based tax evasion in big data EI Scopus SSCI SCIE
期刊论文 | 2019 , 477 , 508-532 | Information Sciences
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Abstract :

© 2018 Elsevier Inc. Affiliated-transaction-based tax evasion (ATTE) is a new strategy in tax evasion that is carried out via legal-like transactions between a group of companies that have heterogeneous, complex and covert interactive relationships to evade taxes. Existing studies cannot effectively detect ATTE behaviors since (i) they perform well only for determining the abnormal financial status of individuals and ineffectively address the interactive relationships among companies, (ii) they aim at detecting ATTE from the perspective of structural characteristics, which leads to a poor false-positive rate, and (iii) few of them perform well in most sectors of companies. Effectively detecting suspicious groups according to both structural characteristics of ATTE groups and business characteristics of ATTE means (BC-ATTEM) remains an open issue. In this paper, we propose an affiliated-parties interest-related network (APIRN) for modeling affiliated parties, interest-related relationships, and their properties for identifying ATTE. Then, we identify the behavioral patterns of ATTE via topological pattern abstraction from APIRN and theoretical inference of BC-ATTEM. Based on the above, we further propose a hybrid method, namely, 3TI, for identifying ATTE suspicious groups via three steps: tax rate differential detection, topological pattern matching and tax burden abnormality identification. Experimental tests that are based on two years of real-world tax data from a province in China demonstrate that 3TI can identify ATTE suspicious groups with higher accuracy and better generality than existing works. Moreover, we identify various interesting implications and provide useful guidance for ATTE inspection based on an analysis of our experimental results.

Keyword :

Affiliated transaction Big data Graph mining Tax evasion

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GB/T 7714 Ruan, Jianfei , Yan, Zheng , Dong, Bo et al. Identifying suspicious groups of affiliated-transaction-based tax evasion in big data [J]. | Information Sciences , 2019 , 477 : 508-532 .
MLA Ruan, Jianfei et al. "Identifying suspicious groups of affiliated-transaction-based tax evasion in big data" . | Information Sciences 477 (2019) : 508-532 .
APA Ruan, Jianfei , Yan, Zheng , Dong, Bo , Zheng, Qinghua , Qian, Buyue . Identifying suspicious groups of affiliated-transaction-based tax evasion in big data . | Information Sciences , 2019 , 477 , 508-532 .
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Measuring student's utilization of video resources and its effect on academic performance EI Scopus
会议论文 | 2018 , 196-198 | 18th IEEE International Conference on Advanced Learning Technologies, ICALT 2018
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Abstract :

Massive video resources were produced to meet the needs of learning knowledge and skills anytime and anywhere through internet. Therefore, whether these video resources were fully utilized by students is an important issue for schools and teachers. This paper proposes three indicators based on student's log data and course's video information to measure the utilization of video resources. In addition, the proposed indicators are applied in a case study to analyze how different utilization patterns affect students' academic performance in a large-scale online distance education context. © 2018 IEEE.

Keyword :

Academic performance Evaluation indicators Log data Online distance education Utilization patterns Video information

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GB/T 7714 He, Huan , Zheng, Qinghua , Dong, Bo et al. Measuring student's utilization of video resources and its effect on academic performance [C] . 2018 : 196-198 .
MLA He, Huan et al. "Measuring student's utilization of video resources and its effect on academic performance" . (2018) : 196-198 .
APA He, Huan , Zheng, Qinghua , Dong, Bo , Yu, Hongchao . Measuring student's utilization of video resources and its effect on academic performance . (2018) : 196-198 .
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IRTED-TL: An Inter-Region Tax Evasion Detection Method Based on Transfer Learning EI Scopus
会议论文 | 2018 , 1224-1235 | 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
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Abstract :

Tax evasion detection plays a crucial role in addressing tax revenue loss. Many efforts have been made to develop tax evasion detection models by leveraging machine learning techniques, but they have not constructed a uniform model for different geographical regions because an ample supply of training examples is a fundamental prerequisite for an effective detection model. When sufficient tax data are not readily available, the development of a representative detection model is more difficult due to unequal feature distributions in different regions. Existing methods face a challenge in explaining and tracing derived results. To overcome these challenges, we propose an Inter-Region Tax Evasion Detection method based on Transfer Learning (IRTED-TL), which is optimized to simultaneously augment training data and induce interpretability into the detection model. We exploit evasion-related knowledge in one region and leverage transfer learning techniques to reinforce the tax evasion detection tasks of other regions in which training examples are lacking. We provide a unified framework that takes advantage of auxiliary data using a transfer learning mechanism and builds an interpretable classifier for inter-region tax evasion detection. Experimental tests based on real-world tax data demonstrate that the IRTED-TL can detect tax evaders with higher accuracy and better interpretability than existing methods. © 2018 IEEE.

Keyword :

Experimental test Feature distribution Interpretability Machine learning techniques Region detection Tax evasions Transfer learning Unified framework

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GB/T 7714 Zhu, Xulyu , Yan, Zheng , Ruan, Jianfei et al. IRTED-TL: An Inter-Region Tax Evasion Detection Method Based on Transfer Learning [C] . 2018 : 1224-1235 .
MLA Zhu, Xulyu et al. "IRTED-TL: An Inter-Region Tax Evasion Detection Method Based on Transfer Learning" . (2018) : 1224-1235 .
APA Zhu, Xulyu , Yan, Zheng , Ruan, Jianfei , Zheng, Qinghua , Dong, Bo . IRTED-TL: An Inter-Region Tax Evasion Detection Method Based on Transfer Learning . (2018) : 1224-1235 .
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Facet Annotation by Extending CNN with a Matching Strategy. PubMed
期刊论文 | 2018 , 30 (6) , 1647-1672 | Neural computation
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Abstract :

Most community question answering (CQA) websites manage plenty of question-answer pairs (QAPs) through topic-based organizations, which may not satisfy users' fine-grained search demands. Facets of topics serve as a powerful tool to navigate, refine, and group the QAPs. In this work, we propose FACM, a model to annotate QAPs with facets by extending convolution neural networks (CNNs) with a matching strategy. First, phrase information is incorporated into text representation by CNNs with different kernel sizes. Then, through a matching strategy among QAPs and facet label texts (FaLTs) acquired from Wikipedia, we generate similarity matrices to deal with the facet heterogeneity. Finally, a three-channel CNN is trained for facet label assignment of QAPs. Experiments on three real-world data sets show that FACM outperforms the state-of-the-art methods.

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GB/T 7714 Wu Bei , Wei Bifan , Liu Jun et al. Facet Annotation by Extending CNN with a Matching Strategy. [J]. | Neural computation , 2018 , 30 (6) : 1647-1672 .
MLA Wu Bei et al. "Facet Annotation by Extending CNN with a Matching Strategy." . | Neural computation 30 . 6 (2018) : 1647-1672 .
APA Wu Bei , Wei Bifan , Liu Jun , Guo Zhaotong , Zheng Yuanhao , Chen Yihe . Facet Annotation by Extending CNN with a Matching Strategy. . | Neural computation , 2018 , 30 (6) , 1647-1672 .
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基于新时代大数据背景下继续教育教与学变革的思考
期刊论文 | 2018 , (20) , 137-139 | 高教学刊
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Abstract :

"要办好继续教育",实现继续教育转型发展,应对即将发生的颠覆性变革,就必须深化教学改革,以学习者为中心,采用个性化教学方式及问题导向学习模式,在开放、共享、智能化学习资源的支撑下,通过"过程性"教学评价,不断提高学习者的学习能力和知识结构的更新,适应新时代社会经济发展要求,进而实现继续教育的可持续发展.

Keyword :

学习者为中心 资源供给 个性化教学 过程性评价

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GB/T 7714 柴学武 , 王晋 . 基于新时代大数据背景下继续教育教与学变革的思考 [J]. | 高教学刊 , 2018 , (20) : 137-139 .
MLA 柴学武 et al. "基于新时代大数据背景下继续教育教与学变革的思考" . | 高教学刊 20 (2018) : 137-139 .
APA 柴学武 , 王晋 . 基于新时代大数据背景下继续教育教与学变革的思考 . | 高教学刊 , 2018 , (20) , 137-139 .
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不同层次护生社区护理就业意向分析
期刊论文 | 2017 , (23) | 全科护理
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Keyword :

西安市 就业意向 社区护理 护生

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GB/T 7714 李娟 , 蒋文慧 . 不同层次护生社区护理就业意向分析 [J]. | 全科护理 , 2017 , (23) .
MLA 李娟 et al. "不同层次护生社区护理就业意向分析" . | 全科护理 23 (2017) .
APA 李娟 , 蒋文慧 . 不同层次护生社区护理就业意向分析 . | 全科护理 , 2017 , (23) .
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论《孙子兵法》的"知彼知己"
期刊论文 | 2017 , (4) , 41-45 | 孙子研究
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Keyword :

理解应用 知彼知己 辩证关系

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GB/T 7714 . 论《孙子兵法》的"知彼知己" [J]. | 孙子研究 , 2017 , (4) : 41-45 .
MLA "论《孙子兵法》的"知彼知己"" . | 孙子研究 4 (2017) : 41-45 .
APA . 论《孙子兵法》的"知彼知己" . | 孙子研究 , 2017 , (4) , 41-45 .
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安康汉滨区农村妇女阴道炎的患病现状
期刊论文 | 2017 , (3) | 延安大学学报(医学科学版)
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Keyword :

农村妇女 阴道炎 筛查

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GB/T 7714 吴宗妍 , 徐优文 , 韩晓兵 . 安康汉滨区农村妇女阴道炎的患病现状 [J]. | 延安大学学报(医学科学版) , 2017 , (3) .
MLA 吴宗妍 et al. "安康汉滨区农村妇女阴道炎的患病现状" . | 延安大学学报(医学科学版) 3 (2017) .
APA 吴宗妍 , 徐优文 , 韩晓兵 . 安康汉滨区农村妇女阴道炎的患病现状 . | 延安大学学报(医学科学版) , 2017 , (3) .
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陕西省孕妇叶酸服用状况分析 CSCD PKU
期刊论文 | 2017 , (2) | 中国公共卫生
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Keyword :

妊娠 膳食补充剂 叶酸

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GB/T 7714 邱惠桢 , 袁淑怡 , 党少农 et al. 陕西省孕妇叶酸服用状况分析 [J]. | 中国公共卫生 , 2017 , (2) .
MLA 邱惠桢 et al. "陕西省孕妇叶酸服用状况分析" . | 中国公共卫生 2 (2017) .
APA 邱惠桢 , 袁淑怡 , 党少农 , 杨姣梅 , 曾令霞 , 颜虹 . 陕西省孕妇叶酸服用状况分析 . | 中国公共卫生 , 2017 , (2) .
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激光导引车模糊控制技术研究
期刊论文 | 2017 , (2) , 12-15+51 | 精密制造与自动化
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Keyword :

轨迹仿真 自动导引车 驱动结构 运动建模

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GB/T 7714 刘保朝 , 宋科 , 暴海宁 . 激光导引车模糊控制技术研究 [J]. | 精密制造与自动化 , 2017 , (2) : 12-15+51 .
MLA 刘保朝 et al. "激光导引车模糊控制技术研究" . | 精密制造与自动化 2 (2017) : 12-15+51 .
APA 刘保朝 , 宋科 , 暴海宁 . 激光导引车模糊控制技术研究 . | 精密制造与自动化 , 2017 , (2) , 12-15+51 .
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