Attribute Reduction of Neighborhood Rough Set Based on Discernment

For neighborhood rough set attribute reduction algorithms based on dependency degree,a neighborhood computation method incorporating attribute weight values and a neighborhood rough set attribute reduction algorithm using discernment as the heuristic information was proposed.The reduction algorithm comprehensively considers the dependency degree and neighborhood granulation degree of attributes,allowing for a more accurate measurement of the importance degrees of attributes.Example analyses and experimental results demonstrate the feasibility and effectiveness of the algorithm.

An improved reduction algorithm based on the degree of attribute discernibility

This paper deals with the problem of attribute discernibility reduction and proposes some new concepts to rough set theory （RST） based on the discernibility matrix of Skowron, such as secondary core, regeneration matrix and the degree of attribute discernibility （DAD）. This paper puts forward an attribute reduction algorithm based on maximum discernibility degree, which opens up an effective way of gaining minimum attribute reduction of decision table. The efficacy of this algorithm has been verified by practical application in a diagnostic system of loader, which substantially decreases information gathering requirement and lowers the overall cost with no loss of accuracy.

A Method for Data Classification Based on Discernibility Matrix and Discernibility Function

A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification. Namely, firstly, we use discernibility matrix and discernibility function to delete superfluous attributes in formation system and get a necessary attribute set. Secondly, we delete superfluous attribute values and get decision rules. Finally, we classify data by means of decision rules. The experiments show that data classification using this method is simpler in the structure, and can improve the efficiency of classification.

Attribute reduction algorithm based on discernibility for decision table

The attribute reduction algorithms of decision table based on discernible matrix are required to construct discernible matrix, which reduces efficiency of algorithms. In this paper, the relationship between attribute discernible matrix and its discernibility is first established for general information systems. Based on the idea that the equivalent discernible matrix has a same attribute reduction, existing matrices are modified and a formula of attribute discernibility associated with algebraic reduction for decision table is proposed. A heuristic attribute reduction algorithm based on attribute discernibility is presented. Experimental results indicate that the algorithm can more easily explore an optimal or sub-optimal reduction, and is efficient.

Customer Asset Risk Discernment of E-commerce Enterprises Based on Case-based Reasoning

In the Internet economy of the twentieth century, the competition for customers between enterprises is stiffer so that they strive for customers by all means. As a kind of new thing in the Internet economy, E-commerce can attract customers and expand sales efficiently; therefore, E-commerce becomes a powerful means by which enterprises can improve customer asset rapidly. However, compared with customer asset of traditional commerce enterprises, E-commerce enterprises customer asset is more liable to be affected by the surroundings, which will result in risk. On the other hand, though enterprises pay close attention to the study of customer asset risk of E-commerce enterprises currently, the academic circles have made little research in this respect, which is not helpful for enterprises to improve customer asset by applying for E-commerce, nor can meet the actual requirement for the development of academic circles. Therefore, the customer asset risk discernment of E-commerce enterprises has been studied in this paper, and case-based reasoning（CBR） has been applied to the discernment of the customer asset risk of E-commerce enterprise, which provides quantitative basis for customer asset risk management of E-commerce enterprises and conduces to the prevention of customer asset risk and the efficiency improvement of E-commerce.

Discerning Travelers

LINGNAN Village in Tonglu County, east China＇s Zhejiang Province. has seen bed and breakfast （B＆B） accommodations flourishing in recent years, with vil- lagers and newcomers alike taking advantage of this promising business. Zhu Zhenhua, from Zhejiang＇s capital city Hangzhou, moved to a village with his wife in 2008. They rented a courtyard property and spent about 300,000 yuan （$46,154） on its renovation. As tourists came to the village and asked whether they could pay to stay in the house, Zhu turned it into a B＆B business.

改良Aldrete量表和DPART在全身麻醉术后复苏病人中的应用效果比较

目的:探讨中文版DPART量表与改良Aldrete量表对全身麻醉病人术后复苏效果的评估效果。方法:以全身麻醉术后入麻醉复苏室(PACU)接受治疗的病人为研究对象,按手术日期先后顺序分为改良Aldrete组和DPART组。改良Aldrete组105例病人采用改良Aldrete作为出室评估工具,DPART组109例病人采用DPART作为出室评估工具,比较两组病人PACU停留时间、出室时疼痛评分、镇静躁动得分、苏醒期躁动发生率、恶心呕吐评分和护士对于两种量表的可行性、实用性评价。结果:DPART组PACU停留时间长于改良Aldrete组(P<0.05),但出室时疼痛评分、恶心呕吐评分低于改良Aldrete组(P<0.05);两组出室时镇静躁动得分及苏醒期躁动发生率比较差异无统计学意义(P>0.05);DPART组量表的可行性评分低于改良Aldrete组(P<0.05),实用性评分高于改良Aldrete组(P<0.05)。结论:应用中文版DPART量表评估PACU病人,病人PACU停留时间较使用改良Aldrete量表评估延长,但病人出室时各项体征表现较好,更有利于保障全身麻醉术后病人安全转出PACU。

基于概念辨析的我国历史地段的内涵及分类探析

文章首先梳理了文化遗产保护领域的国际宪章、公约、宣言等国际文件和英国、法国、意大利、日本、美国、澳大利亚等6个历史遗产保护代表性国家以及我国历史地段相关概念的产生过程,其次从适用范围、内涵范畴、概念类型、内容分类4个方面对其进行解读与对比,最后根据内容解读与对比,对我国历史地段的保护层次与内涵、内容分类及分级进行思考与探索。文章建议将我国“历史地段”概念调整为“历史(文化)地段”以及对应的英文翻译,勾勒了2个等级10种分类的历史文化地段内容框架,以期对未来城乡历史文化保护传承体系中的历史地段概念的判定与保护有所裨益。

在线健康平台信息质量与可读性计量分析

[目的/意义]在线健康平台信息质量与可读性水平的高低直接影响着社会大众对健康信息的利用效果。对在线健康平台信息质量水平与可读性进行计量分析,有助于揭示在线健康平台信息的现状及可改进之处,这对今后更为有效地帮助社会大众构建和提升健康信息素养具有重要意义。[方法/过程]本文运用DISCERN健康信息质量评价工具,并改进现有中文健康信息可读性计算公式对在线健康平台信息代表样本进行质量与可读性分析研究。[结果/结论]研究发现,目前我国在线健康平台信息整体质量接近中等水平,信息间可读性值差异显著,且与质量水平存在正相关关系。此外,不同来源平台与不同提供主体间的健康信息在质量与可读性上均有差异。

Reduction Algorithms Based on Discernibility Matrix:The Ordered Attributes Method

In this paper, we present reduction algorithms based on the principle of Skowron's discernibility matrix - the ordered attributes method. The completeness of the algorithms for Pawlak reduct and the uniqueness for a given order of the attributes are proved. Since a discernibility matrix requires the size of the memory of U2, U is a universe of objects, it would be impossible to apply these algorithms directly to a massive object set. In order to solve the problem, a so-called quasi-discernibility matrix and two reduction algorithms are proposed. Although the proposed algorithms are incomplete for Pawlak reduct, their opimal paradigms ensure the completeness as long as they satisfy some conditions. Finally we consider the problem on the reduction of distributive object sets.

略论思辨性阅读的内涵、路径与意义

思辨即批判性思维,本质是理性的反思。思辨性阅读是借助批判性思维的原理、策略与方法而展开的旨在追求合理断言的阅读。在思辨性阅读中,文本是思辨的前提与基础,文本的客观性与独立性,既是对思辨的理性约束,也激发读者思辨求真。思辨性阅读是一个不断质疑、探究的过程,其一般路径是:文本实证(读文)→作者意图探究(读人)→自我反思(读我),以文本反思促进学生的自我反思,培养其实证探究能力与理性开放的精神品质。思辨的意义在于对话与融合,在思辨中才能达成读者与文本的对话、工具性与人文性的融合,而对话与融合正是语言实践的最大价值,也是阅读教学应该追求的最高境界。

基于DISCERN算法筛选影响肉鸡脂肪沉积的关键基因

选取法国高低脂2组7周龄肉鸡腹部脂肪的RNA测序转录组数据中的17934个基因,采用差分稀疏调节网络(differential sparsE regulatory network,DISCERN)算法对相应数据进行分析,以期筛选出影响肉鸡腹部脂肪沉积的关键基因,并识别肉鸡不同基因表达数据之间网络差异关系,推断基因调控依赖网络的信息拓扑变化。结果显示,通过DISCERN算法发现HCN4、NPPC、UCN3等基因在17934个基因得分排序中得分相对较高,推断NPPC、HCN4、UCN3等基因可能是影响肉鸡腹部脂肪沉积的关键基因。本试验采用DISCERN算法,剖析网络结构变化,通过对基因网络进行量化分析,对农业动物转录组测序数据分析方法进行了新的尝试和创新。

基于证据理论的多层超网络影响力节点识别方法

针对多层超网络研究多集中于拓扑结构,且影响力节点识别方法中涉及指标较为单一,无法全面准确识别影响力节点的情况,提出一种基于证据理论的多层超网络影响力节点识别方法。首先,在多层超网络拓扑结构基础上,根据聚合网络思想构建多层聚合超网络;其次,基于证据理论定义问题的辨识框架;最后,利用D-S(Dempster-Shafer)证据组合方法,融合网络的局部、位置和全局指标以识别网络影响力节点。将该方法应用于arXiv数据集构建的物理−计算机科学双层科研合作超网络(MAH),在基于RP(Reactive Process)和CP(Contact Process)策略的易感−感染−易感(SIS)超网络传播模型中,与超度中心性、K-shell、接近中心性方法等相比,传播速度最快,且最先达到稳态;隔离影响力排名前6%节点后,网络平均超度、聚类系数以及网络效率均减小;随着隔离影响力节点比例的增大,网络子图数量增速与接近中心性方法相近;通过单调性指标值度量识别结果粗粒度,达到0.9998,识别结果具有较高区分度。综合多个实验结果,表明该多层超网络影响力节点识别方法准确有效。

基于依赖空间的对象导出三支概念格的属性约简

在给定形式背景下,基于依赖空间提出了对象导出三支概念格属性约简的新定义,在此基础上讨论了属性约简方法。首先,借助三支算子定义了对象幂集上的一致关系,引入依赖空间。通过依赖空间生成闭包算子的闭元素,研究了闭元素和对象导出三支概念的外延之间的关系。其次,提出基于依赖空间的对象导出三支概念格属性约简的定义,该定义下的约简集是保持由原属性集确定的一致关系不变的最小属性子集。最后,给出协调集的判定定理,利用可辨识属性矩阵及辨识函数给出对象导出三支概念格的属性约简方法。

Generalized binary discernibility matrix for attribute reduction in incomplete information systems

To extract and express the knowledge hidden in information systems, discernibility matrix and its extensions were introduced and applied successfully in many real life applications. Binary discernibility matrix, as a representative approach, has many interesting superior properties and has been rapidly developed to find intuitive and easy to understand knowledge. However, at present, the binary discernibility matrix is mainly adopted in the complete information system. It is a challenging topic how to achieve the attribute reduction by using binary discernibility matrix in incomplete information system. A form of generalized binary discernibility matrix is further developed for a number of representative extended rough set models that deal with incomplete information systems. Some useful properties and criteria are introduced for judging the attribute core and attribute relative reduction. Thereafter, a new algorithm is formulated which supports attribute core and attribute relative reduction based on the generalized binary discernibility matrix. This algorithm is not only suitable for consistent information systems but also inconsistent information systems. The feasibility of the proposed methods was demonstrated by worked examples and experimental analysis.

基于正域向量的决策粗糙集属性约简

在决策粗糙集模型中,现有划分层的正域都是通过集合求并所得,但基于该方法的保正域不变的属性约简与基于差别矩阵方法所得约简结果并不一致。提出了一种基于正域向量的决策粗糙集属性约简方法,该方法与基于差别矩阵的约简方法所得结果是一致的。最后给出一个算例说明其一致性。

Investigation on AQ11, ID3 and the Principle of Discernibility Matrix

The principle of discernibility matrix serves as a tool to discuss and analyze two algorithms of traditional inductive machine learning, AQ11 and ID3. The results are: (1) AQ11 and its family can be completely specified by the principle of discernibility matrix; (2) ID3 can be partly, but not naturally, specified by the principle of discernibility matrix; and (3) The principle of discernibility matrix is employed to analyze Cendrowska sample set, and it shows the weaknesses of knowledge representation style of decision tree in theory.

程红亮基于“辨经论治”理论治疗血管性痴呆探析

程红亮教授认为,血管性痴呆病位在脑,与督、任、心、肾密切相关,明确提出“督-任-脑-心-肾”五位一体元神论。程红亮教授认为,其主要病机为“元阳虚衰、痰瘀阻窍”,以元阳虚衰、相关脏腑阳气不足为本,痰浊、瘀血闭阻气血经络神窍为标,属本虚标实之证,主张应在“督、任、脑、心、肾”五者的紧密联系基础上辨经论治血管性痴呆,总结并提出“百会、风府、神庭、大椎”“关元、气海”“内关、神门”和“中冲、涌泉”4对核心组穴及其他组穴,在临床上治疗血管性痴呆疗效显著。

一般决策形式背景的属性约简

决策形式背景是形式背景的重要扩展。属性约简是决策形式背景领域研究的热点问题。由现实数据所构建的决策形式背景通常是不一致的,文中面向实际应用,研究一般决策形式背景的广义属性约简方法。定义了一般决策形式背景的广义属性约简,并基于辨识函数给出了计算所有约简的算法。该算法具有良好的通用性,可应用于一致和不一致的决策形式背景。

基于信息粒的不协调决策形式背景的分布约简

粒计算和知识约简是知识发现和数据挖掘的两个重要课题。基于信息粒研究不协调决策形式背景的属性约简的定义和方法。首先,利用对象概念的内涵定义对象集上的拟序关系,并研究其相关性质。然后,利用拟序类定义分布函数和最大部分函数,进而提出不协调决策形式背景的(最大)分布协调集和(最大)分布约简的定义。最后,定义不协调决策形式背景的(最大)分布辨识矩阵及(最大)分布辨识公式,基于辨识矩阵给出(最大)分布协调集的判定定理,并提出计算分布约简和最大分布约简的方法。