概念空间中上下位关系的意义识别研究

针对上下位关系在分类层级结构建立阶段遇到的多义性问题,给出一种概念空间中上下位关系意义识别的方法.单个概念的意义识别问题被转换为概念空间中上下位关系的意义识别.首先利用并列语境解决语境稀疏问题,获取上下位关系意义的语境.然后利用<同义词词林>对每个语境进行词义修正,以三种特征计算特征词权重,构建"关系一词'的高维向量空间,然后通过潜在语义分析降维,获取上下位关系意义的潜在语义,最后组平均聚类后得到关系的意义划分.在实验中,给出了聚类阈值自动调整函数,分析了词林和潜在语义分析的作用,实验结果证实了方法的有效性.     

Intuitionistic fuzzy transformation semigroups

The idea of (faithful) intuitionistic fuzzy transformation semigroup, intuitionistic admissible relation, and intuitionistic (strong) homomorphism are introduced and their basic properties are examined.     

Uniqueness of the Perfect Fusion Grid on ℤ d

Region merging methods consist of improving an initial segmentation by merging some pairs of neighboring regions. In a graph, merging two regions, separated by a set of vertices, is not straightforward. The perfect fusion graphs defined in J. Cousty et al. (J. Math. Imaging Vis. 30:(1):87–104, 2008) verify all the basic properties required by region merging algorithms as used in image segmentation. Unfortunately, the graphs which are the most frequently used in image analysis (namely, those induced by the direct and the indirect adjacency relations) are not perfect fusion graphs. The perfect fusion grid, introduced in the above mentioned reference, is an adjacency relation on ℤ ^d which can be used in image analysis, which indeed induces perfect fusion graphs and which is “between” the graphs induced by the direct and the indirect adjacencies. One of the main results of this paper is that the perfect fusion grid is the only such graph whatever the dimension d.

基于改进灰色理论的威胁指标权重技术

针对各种网络指标之间的相互影响,同时考虑主客观2个方面的因素,提出用灰色理论中的灰关联度和传统层次分析法相结合的算法进行网络威胁指标权重的确定。实验证明,该方法数学理论严谨,具有良好的实用价值,使网络威胁评估方法在可信度方面有一定的 提高。     

不完备信息系统中对象的相似性刻画

信息系统知识约简与知识发现是粗糙集理论的重要研究方向。通过对不完备信息系统中对象的相似性刻画方式以及相应的粗糙集模型进行对比分析,基于限制容差关系提出了一种新的限制相似关系,建立了基于限制相似关系的粗糙集模型,讨论了模型的基本性质及其与已有模型之间的关系。     

On the finite and general implication problems of independence atoms and keys

We investigate implication problems for keys and independence atoms in relational databases. For keys and unary independence atoms we show that finite implication is not finitely axiomatizable, and establish a finite axiomatization for general implication. The same axiomatization is also sound and complete for finite and general implication of unary keys and independence atoms, which coincide. We show that the general implication of keys and unary independence atoms and of unary keys and general independence atoms is decidable in polynomial time. For these two classes we also show how to construct Armstrong relations. Finally, we establish tractable conditions that are sufficient for certain classes of keys and independence atoms not to interact.     

Single Criterion Net Flow Using Concordance and Discordance Relations

This article proposes a flow-based method using the single criterion net flow for pattern classification. Traditional single criterion net flow, generated on the basis of net partial concordance indices, measures the preference intensity for one pattern with respect to all others on this criterion. A concordance index measures the intensity of preference for one pattern over another pattern. Contrary to traditional flow-based methods, such as PROMETHEE, in which only the concordance relation is taken into account, the proposed method proposes a new definition of single criterion net flow using both concordance and discordance relations. This can balance pros and cons for the preference of one pattern over another pattern for a criterion. The final classification decision for a new pattern depends on its net flow. Criteria weights are determined using a genetic-algorithm-based approach. Empirical results involving bankruptcy prediction demonstrate that the proposed method performs well compared to other well-known classification methods.     

A consensus model for hesitant fuzzy preference relations and its application in water allocation management

This paper investigates a consensus model for hesitant fuzzy preference relations (HFPRs). First, we present a revised definition of HFPRs, in which the values are not ordered for the hesitant fuzzy element. Second, we propose an additive consistency based estimation measure to normalize the HFPRs, based on which, a consensus model is developed. Here, two feedback mechanisms are proposed, namely, interactive mechanism and automatic mechanism, to obtain a solution with desired consistency and consensus levels. In the interactive mechanism, the experts are suggested to give their new preference values in a specific range. If the experts are unwilling to offer their updated preferences, the automatic mechanism could be adopted to carry out the consensus process. Induced ordered weighted averaging (IOWA) operator is used to aggregate the individual HFPRs into a collective one. A score HFPR is proposed for collective HFPR, and then the quantifier-guided dominance degrees of alternatives by using an OWA operator are obtained to rank the alternatives. Finally, both a case of study for water allocation management in Jiangxi Province of China and a comparison with the existing approaches are carried out to show the advantages of the proposed method.     

基于模式的远监督关系抽取算法

远监督关系抽取算法能够自动将关系库中的关系与无标注的文本对齐,以进行文本中的关系抽取。目前提出的远监督关系抽取算法中,大多数是基于特征的。然而,此类算法在将实例转换为特征时,经常会出现关键信息不突出、数据集线性不可分等问题,影响关系抽取的效果。该文提出了一种基于模式的远监督关系抽取算法,其中引入了基于模式的向量,并使用了基于核的机器学习算法来克服上述问题。实验结果表明,该文提出的基于模式的远监督关系抽取算法,能够有效地提升远监督关系抽取的准确率。     

基于属性约简的应用服务器优化算法改进

优化参数配置是优化应用服务器性能的重要方面;基于传统参数调节的优化策略耗时耗力缺乏系统性和规律性;利用模块化思想针对目标决策函数对应用服务器参数进行分类,可构建条件属性约简模型;基于属性约简的应用服务器优化算法,可去除对于目标决策函数相对不重要的参数,并获得相对重要的参数,从而达到锁定目标重点调节,快速提高系统性能的目的;现有的约简模型优化算法多基于经典粗糙集理论,在等价关系的基础上构造分类,容易造成大量的信息破坏和流失;文章通过拓展等价关系到一般二元关系,利用广义粗糙集理论改良了基于模块化思想和属性约简模型的应用服务器优化算法,通过定义辨识函数对条件属性进行约简,再结合依赖度计算,得到最终目标参数。