基于语义相似度的Web数据库不精确查询方法

为了解决普通用户对于Web数据库的不精确查询问题,提出了一种基于语义相似度的Web数据库不精确查询方法。对于一个给定查询,该方法首先在查询历史中找出一个(或若干)与其相似度高于给定放松阈值的查询,然后从数据库中找出与这些查询相匹配的元组作为当前查询的不精确查询的结果,最后将这些查询结果按其对初始查询的满足程度进行排序。实验结果表明,提出的不同查询之间的语义相似度评估方法性能稳定、评估结果合理,不精确查询方法具有较高的查全率和排序准确性。     

非精确任务集的容错EDF调度

该文将容错EDF调度算法和非精确计算技术结合起来,提高了算法的调度性能,使单处理器系统正常运行时具有高吞吐量,同时,在出现一个或多个偶发性软件错误时,仍能满足系统中关键任务的时限要求。     

基于Ticket探测的非精确单播路由算法仿真

TBP(Ticket-based Probing)算法是一种有效的非精确网络状态下单播路由算法.它具有较好的可行性,并且优化了平均路由代价,但仿真时该算法仅针对均匀分布的网络时延变化,因此在应用时有一定的局限性.本文仿真分析了其在均匀分布和正态分布两种时延变化模型下算法的性能,以及不同探测包生成方案对算法性能的影响.仿真结果表明,TBP算法在正态分布下的寻路成功率通常比均匀分布下的要低,而不同探测包生成方案对算法性能各指标的影响各有不同.     

基于不精确信息实例检索模型的研究

传统实例检索模型缺乏对不确定环境中不精确信息的适应性。采用构造因果网络的分阶段实例检索模型,则可以有效地处理实例检索中的不精确性,并能提高基于实例推理系统的性能。     

模糊回溯法实现高校多级多校区分布式网络排课

高校扩招,人数增加,异地校区增多,排课复杂度增加。本文以茂名学院的排课管理的实际情况为背景,先分析了排课的约束条件和要达到的排课效果,把众多约束条件整合到由时间和空间组成的二维空间中,采用模糊回溯法实现了高校多级多校区网络系统环境下分布式排课。该排课算法具有较强的普遍适应性和适用性。     

A QoS Multicast Routing Algorithm Working with Imprecise State Information

In large networks, maintaining precise global network state information is almost impossible. Many factors, including non-negligible propagation delay, infiequent link state update due to overhead concerns, link state update policy, and hierarchical topology aggregation, have impacts on the precision of the network state information. The existing QoS multicast routing algorithms do not provide satisfactory performance with imprecise state information. In this paper, we propose a distributed QoS multicast routing scheme based on traffic lights, called QMRI algorithm, which can probe multiple feasible tree branches, and select the optimal or near-optimal branch through the UR or TL mode for constructing a multicast tree with QoS guarantees if it exists. The proposed algorithm considers not only the QoS requirements but also the cost optimality of the multicast tree. Extensive simulations show that our algorithm achieves high call-admission ratio and low-cost multicast trees with modest message overhead. The algorithm can tolerate high degree of state information imprecision.     

基于非精确状态的蚂蚁网络在QoS路由选择中的应用

简要介绍了一种描述网络的非精确状态以及计算给定路径满足QoS的概率的方法和将基本的蚂蚁网络机制扩展为基于约束的选路的方法。结合前两者本文提出了一种基于蚂蚁网络并考虑了网络非精确性的QoS路由选择算法,即QRANP算法。     

Imprecise probability trees: Bridging two theories of imprecise probability

We give an overview of two approaches to probability theory where lower and upper probabilities, rather than probabilities, are used: Walley's behavioural theory of imprecise probabilities, and Shafer and Vovk's game-theoretic account of probability. We show that the two theories are more closely related than would be suspected at first sight, and we establish a correspondence between them that (i) has an interesting interpretation, and (ii) allows us to freely import results from one theory into the other. Our approach leads to an account of probability trees and random processes in the framework of Walley's theory. We indicate how our results can be used to reduce the computational complexity of dealing with imprecision in probability trees, and we prove an interesting and quite general version of the weak law of large numbers.     

CIRCE: Correcting Imprecise Readings and Compressing Excrescent points for querying common patterns in uncertain sensor streams

Continuous sensor stream data are often recorded as a series of discrete points in a database from which knowledge can be retrieved through queries. Two classes of uncertainties inevitably happen in sensor streams that we present as follows. The first is Uncertainty due to Discrete Sampling (DS Uncertainty); even if every discrete point is correct, the discrete sensor stream is uncertain – that is, it is not exactly like the continuous stream – since some critical points are missing due to the limited capabilities of the sensing equipment and the database server. The second is Uncertainty due to Sampling Error (SE Uncertainty); sensor readings for the same situation cannot be repeated exactly when we record them at different times or use different sensors since different sampling errors exist. These two uncertainties reduce the efficiency and accuracy of querying common patterns. However, already known algorithms generally only resolve SE Uncertainty. In this paper, we propose a novel method of Correcting Imprecise Readings and Compressing Excrescent (CIRCE) points. Particularly, to resolve DS Uncertainty, a novel CIRCE core algorithm is developed in the CIRCE method to correct the missing critical points while compressing the original sensor streams. The experimental study based on various sizes of sensor stream datasets validates that the CIRCE core algorithm is more efficient and more accurate than a counterpart algorithm to compress sensor streams. We also resolve the SE Uncertainty problem in the CIRCE method. The application for querying longest common route patterns validates the effectiveness of our CIRCE method.     

A workbench for computational geometry

We describe the design and implementation of a workbench for computational geometry. We discuss issues arising from this implementation, including comparisons of different algorithms for constant factors, code size, and ease of implementation. The workbench is not just a library of computational geometry algorithms and data structures, but is designed as a geometrical programming environment, providing tools for: creating, editing, and manipulating geometric objects; demonstrating and animating geometric algorithms; and, most importantly, for implementing and maintaining complex geometric algorithms.This research was partially supported by the Natural Sciences and Engineering Research Council of Canada, Carleton University, and the Univeristy of Passau. Work on this project was carried out in part while A. Knight and J.-R. Sack were at the University of Passau.     

An optimal algorithm for the boundary of a cell in a union of rays

In this paper we study a cell of the subdivision induced by a union ofn half-lines (or rays) in the plane. We present two results. The first one is a novel proof of theO(n) bound on the number of edges of the boundary of such a cell, which is essentially of methodological interest. The second is an algorithm for constructing the boundary of any cell, which runs in optimal (n logn) time. A by-product of our results are the notions of skeleton and of skeletal order, which may be of interest in their own right.This work was partly supported by CEE ESPRIT Project P-940, by the Ecole Normale Supérieure, Paris, and by NSF Grant ECS-84-10902.This work was done in part while this author was visiting the Ecole Normale Supérieure, Paris, France.     

An in-place algorithm for Klee's measure problem in two dimensions

We present the first in-place algorithm for solving Klee's measure problem for a set of n axis-parallel rectangles in the plane. Our algorithm runs in O(n3/2logn) time and uses O(1) extra words in addition to the space needed for representing the input. The algorithm is surprisingly simple and thus very likely to yield an implementation that could be of practical interest. As a byproduct, we develop an optimal algorithm for solving Klee's measure problem for a set of n intervals; this algorithm runs in optimal time O(nlogn) and uses O(1) extra space.     

Approximation algorithms for terrain guarding

We present approximation algorithms and heuristics for several variations of terrain guarding problems, where we need to guard a terrain in its entirety by a minimum number of guards. Terrain guarding has applications in telecommunications, namely in the setting up of antenna networks for wireless communication. Our approximation algorithms transform the terrain guarding instance into a Minimum Set Cover instance, which is then solved by the standard greedy approximation algorithm [J. Comput. System Sci. 9 (1974) 256-278]. The approximation algorithms achieve approximation ratios of O(logn), where n is the number of vertices in the input terrain. We also briefly discuss some heuristic approaches for solving other variations of terrain guarding problems, for which no approximation algorithms are known. These heuristic approaches do not guarantee non-trivial approximation ratios but may still yield good solutions.     

Parameterized complexity and improved inapproximability for computing the largest j-simplex in a V-polytope

We consider the problem of computing the squared volume of the largest j-simplex contained in an n-dimensional polytope presented by its vertices (a V-polytope). We show that the related decision problem is W[1]-complete, with respect to the parameter j. We also improve the constant inapproximability factor given in [A. Packer, Polynomial-time approximation of largest simplices in V-polytopes, Discrete Appl. Math. 134 (1-3) (2004) 213-237], by showing that there are constants μ<1,c>1 such that it is NP-hard to approximate within a factor of cμn the volume of the largest ⌊μn⌋-simplex contained in an n-dimensional polytope with O(n) vertices.     

The drawability problem for minimum weight triangulations

A graph is minimum weight drawable if it admits a straight-line drawing that is a minimum weight triangulation of the set of points representing the vertices of the graph. We study the problem of characterizing those graphs that are minimum weight drawable. Our contribution is twofold: We show that there exist infinitely many triangulations that are not minimum weight drawable. Furthermore, we present non-trivial classes of triangulations that are minimum weight drawable, along with corresponding linear time algorithms that take as input any graph from one of these classes and produce as output such a drawing. One consequence of our work is the construction of triangulations that are minimum weight drawable but not Delaunay drawable – that is, not drawable as a Delaunay triangulation.     

确定两个任意简单多边形空间关系的算法

阐述了把简单多边形的边分为奇偶边的新思想,根据一多边形的边与另一多边形的拓朴关系,划分边为5种拓朴类型:内边、外边、重叠边、相交边、复杂边,进而给出了确定两个多边形空间关系的算法,算法的时间复杂度为O((n+m)log(n+m)),其中n、m分别是两输入多边形的顶点数。该算法建立在数学理论基础之上,没有奇异情况需要处理,易于编程实现。算法的主要思想对确定两个简单多面体空间关系亦有参考价值。     

Clustering methods for geometric objects and applications to design problems

Clustering of geometric objects is a very familiar and important problem in many different areas of applications as well as in the theoretical foundation of some modern fields of computer science. This paper describes how design problems, especially the design of an assembly line, can be transformed into a clustering problem. In order to solve the problem for large sizes of input data we introduce a structure, called Voronoi Tree, which applied to our real world data (assembly line design) did not only reduce the time to get a feasible design of an assembly line dramatically, but additionally increased the value of the design by more than 30% (in comparison with standard design methods). In addition to this we introduce a clustering method which is of interest for those applications which can be transformed to planar clustering problems. In this particular case it is possible to compute an (hierarchically) optimized clustering with resp. to a large class of clustering measures in timeO(nn^1/2log³ n+U _F(n)nn^1/2+P _F(n)) [n: number of points;U _F(n), P_F(n) dependent on the chosen clustering measure].     

The slab dividing approach to solve the EuclideanP-Center problem

Givenn demand points on the plane, the EuclideanP-Center problem is to findP supply points, such that the longest distance between each demand point and its closest supply point is minimized. The time complexity of the most efficient algorithm, up to now, isO(n ² p–1· logn). In this paper, we present an algorithm with time complexityO(n ⁰(P)).     

The searching over separators strategy to solve some NP-hard problems in subexponential time

In this paper we propose a new strategy for designing algorithms, called the searching over separators strategy. Suppose that we have a problem where the divide-and-conquer strategy can not be applied directly. Yet, also suppose that in an optimal solution to this problem, there exists a separator which divides the input points into two parts,A _d andC _d, in such a way that after solving these two subproblems withA _d andC _d as inputs, respectively, we can merge the respective subsolutions into an optimal solution. Let us further assume that this problem is an optimization problem. In this case our searching over separators strategy will use a separator generator to generate all possible separators. For each separator, the problem is solved by the divide-and-conquer strategy. If the separator generator is guaranteed to generate the desired separator existing in an optimal solution, our searching over separators strategy will always produce an optimal solution. The performance of our approach will critically depend upon the performance of the separator generator. It will perform well if the total number of separators generated is relatively small. We apply this approach to solve the discrete EuclideanP-median problem (DEPM), the discrete EuclideanP-center problem (DEPC), the EuclideanP-center problem (EPC), and the Euclidean traveling salesperson problem (ETSP). We propose algorithms for the DEPM problem, the DEPC problem, and the EPC problem, and we propose an algorithm for the ETSP problem, wheren is the number of input points.This research work was partially supported by the National Science Council of the Republic of China under Grant NSC 79-0408-E007-04.     

Algorithm for constrained delaunay triangulation

A direct algorithm for computing constrained Delaunay triangulation in 2-D is presented. The algorithm inserts points along the constrained edges (break lines) to maintain the Delaunay criterion. Since many different insertions are possible, the algorithm computes only those that are on the Delaunay circles of each intersected triangle. A shelling procedure is applied to put triangles together in such a way that completeness and correctness are guaranteed.