一种基于概念格属性约简的本体合并方法

提出一种基于概念格属性约简的本体合并方法。该方法先对源本体中的概念进行外延和内涵的分析,以此为形式背景构造概念格。对所构造的概念格进行属性约简,删除本体合并中的冗余信息,约简绝对不必要属性,以最少的信息精确地反映概念格及本体的本质和结构。最后通过实例分析此方法的可行性。     

An Abstract Reachability Approach by Combining HOL Induction and Multiway Decision Graphs

In this paper, we provide a necessary infrastructure to define an abstract state exploration in the HOL theorem prover. Our infrastructure is based on a deep embedding of the Multiway Decision Graphs (MDGs) theory in HOL. MDGs generalize Reduced Ordered Binary Decision Diagrams (ROBDDs) to represent and manipulate a subset of first-order logic formulae. The MDGs embedding is based on the logical formulation of an MDG as Directed Formulae (DF). Then, the MDGs operations are defined and the correctness pro...     

Versioning XML-based office documents

The ability to reliably merge independent updates of a document is a crucial prerequisite to efficient collaboration in office work. However, merge support for common office document standards like OpenDocument or OfficeOpenXML is still in its infancy. In this paper, we present a consistent versioning model for XML documents in general including merge support. This is achieved by using context-aware fingerprints that identify edit operations and allow for a conflict detection. We show how to extract tracked changes from office documents and map them on our delta model. Experimental results indicate that our fingerprinting technique is efficient and reliable.     

A new algebraic structure for formal concept analysis

Formal concept analysis (FCA) originally proposed by Wille [39], is an important theory for data analysis and knowledge discovery. Concept lattice is the core of the mathematical theory of formal concept analysis. To address the requirements of real word applications, concept lattice has been extended to many other forms from the theoretical point of view and possible applications. In this paper, with the aim of deriving the mathematical properties of formal concepts from the point of algebra, we propose a new algebra system for the formal context. Under the frame of the proposed system, some interesting properties of formal concepts are explored, which could be applied to explore concept hierarchy and ontology merging.     

Improving the spatio-temporal distribution of surface solar radiation data by merging ground and satellite measurements

Appropriate information on solar resources is very important for a variety of technological areas, such as: agriculture, meteorology, forestry engineering, water resources and in particular in the designing and sizing of solar energy systems. However, the availability of observed solar radiation measurements has proven to be spatially and temporally inadequate for many applications. In this paper we propose to merge the global solar radiation measurements from the Royal Meteorological Institute of Belgium solar measurements network with the operationally derived surface incoming global short-wave radiation products from Meteosat Second Generation satellites imageries to improve the spatio-temporal resolution of the surface global solar radiation data over Belgium. We evaluate several merging methods with various degrees of complexity (from mean field bias correction to geostatistical merging techniques) together with interpolated ground measurements and satellite-derived values only. The performance of the different methods is assessed by leave-one-out cross-validation.     

排序算法在龙芯3A上的优化实现

分析归并排序算法和快速排序算法,根据国产CPU龙芯3A的体系结构特性,提出2种优化算法并进行实现。综合利用访存特性,引入拷贝优化、循环展开、交换操作优化和不同基本排序混用等优化技术。测试结果表明,在不影响排序稳定性的前提下,与Glibc 2.11库中的排序函数相比,2种优化算法均能提升16.9%~90.5%的排序性能。     

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.

快速搜索与发现密度峰值聚类算法的优化研究

CFSFDP是基于密度的新聚类算法,可聚类非球形数据集,具有聚类速度快实现简单等优点。CFSFDP需人工尝试确定密度阈值dc且对一个类中存在多密度峰值的数据无法进行准确聚类,为解决该缺点,本文提出基于近邻距离曲线和类合并优化CFSFDP（简称 NM-CFSFDP）的聚类算法。首先,算法用近邻距离曲线变化情况自动确定密度阈值dc;然后,用本文提出自动确定dc的CFSFDP对数据聚类;最后用本文计算dc值的方法指导类的合并,引入内聚程度衡量参数解决了类合并后不能撤销的难题,从而实现对多密度峰值数据的正确聚类。通过实验对比,NM-CFSFDP算法确实比CFSFDP算法具有更加精确的聚类效果。     

一种面向非平衡数据的多簇IB算法

信息瓶颈(Information Bottleneck,IB)方法在处理非平衡数据集时,倾向于将大簇中的数据对象划分到数据规模较小的小簇中,造成了聚类效果不理想的问题。针对该问题,提出了一种面向非平衡数据的多簇信息瓶颈算法(McIB)。McIB算法采用向下抽样方法来降低非平衡数据集的倾斜度,使用先划分再学习后合并的策略来优化IB算法处理非平衡数据的合并抽取过程。整个算法包含3步:首先根据分离标准来确定抽样比例参数;然后对数据进行初步的聚类,生成可信赖的多个簇;最后再利用簇之间的相似性对簇进行合并,组织多个簇代表每个实际的簇来得到最终的聚类结果。实验结果表明:所提算法能够有效地解决IB方法在非平衡数据集上的“均匀效应”问题;与其他聚类算法相比,McIB算法的性能更优。     

基于网格的快速搜寻密度峰值的聚类算法优化研究

CFSFDP是基于密度的新型聚类算法,可聚类非球形数据集,具有聚类速度快、实现简单等优点。然而该算法在指定全局密度阈值dc时未考虑数据空间分布特性,导致聚类质量下降,且无法对多密度峰值的数据集准确聚类。针对以上缺点,提出基于网格分区的CFSFDP(简称GbCFSFDP)聚类算法。该算法利用网格分区方法将数据集进行分区,并对各分区进行局部聚类,避免使用全局dc,然后进行子类合并,实现对数据密度与类间距分布不均匀及多密度峰值的数据集准确聚类。两个典型数据集的仿真实验表明,GbCFSFDP算法比CFSFDP算法具有更加精确的聚类效果。