一种互联网海量情报规则优化方法

现在很多部门都需要通过规则处理海量情报数据,规则的数量一旦达到海量级规模,对规则的处理技术的要求将会变得越来越高,海量规则的优化将是一个十分重要的问题.文中展示了一种海量规则的优化方法.若两个规则网最后的计算结果是一样的,则可以认为这两个规则网是等价的.基于该等价规则模块的变换可以将代价小的规则模块替换掉代价大的规则模块,从而以后可以选择一种代价最小的规则模块.本文提出规则网模块等价替换的5种优化方法,并对其做了相应的证明.通过优化,可以使得海量规则网处于计算代价尽量最小状态,以此减少处理机的计算工作量.分析表明,通过等价规则替换,可以大大提高规则处理效率.     

Cognitive-bias toward gaming-related words and disinhibition in World of Warcraft gamers

This study investigated cognitive biases toward gaming-related words and differences in cognitive performance among twelve World of Warcraft players (WWP) and thirty non-players (NP). We measured response to valenced common English and WoW jargon words using a computer-based go/no-go task. Sometimes positive valence words were the targets for the ‘go’ response, with negative-valence words as the distracters, sometimes the reverse. Target discrimination (d′) and response disinhibition (C) were calculated using a signal detection analysis. Based on questionnaire responses, there were no differences between groups in depression, anxiety, smoking or drinking, but WWP reported significantly more screen and gaming time (17.31 h/week versus 4.12 among NP). WWP had faster reaction time (RT) and better discrimination of targets from distracters (high d′) but also showed higher disinhibition (low C). WWP also showed cognitive-bias toward game-related words in the form of higher d′ for WoW jargon than common English and more disinhibition to positive-valence WoW jargon. Similar to past studies which have found alcoholics to have cognitive biases toward alcohol-related words, WWP who play frequently showed cognitive biases toward words related to the World of Warcraft game.     

Some new error inequalities for a generalized quadrature rule of open type

Some new error inequalities for a generalized quadrature rule of open type are established. Especially, two sharp inequalities are derived when n is an odd and an even integer, respectively.     

基于OWL本体的UML类图推理

分析UML模型一致性检测的研究意义,以及UML类图推理的研究现状,提出一种基于OWL本体的UML类图推理方案.研究UML类图向OWL本体转换的映射规则,给出UML类图包含关系、可满足性、等价关系和相离关系的判断方法及其推理规则.利用Jena推理机制实现了UML类图包含关系、可满足性、等价关系和相离关系的推理.     

关联规则挖掘在航空安全报告分析中的应用

针对航空安全自愿报告的特点,将关联规则挖掘算法中改进的Apriori算法应用于航空安全报告。提出用规则前后件约束的方法挖掘异常事件和事件原因之间的关联规则,不但限制冗余规则的生成,还进一步提高了挖掘的效率和精度。依据生成的频繁项集对引起航空事件的主要原因进行分析,总结了一些对提高民航安全水平有价值的决策信息。     

基于参考点和投票规则的多目标粒子群优化群体决策

针对巨量可选方案的群体决策问题,提出了一个新的基于参考点和投票规则的多目标粒子群优化算法。该算法把个体与参考点的支配关系或者距离作为一个重要因素,在选择引导者的锦标赛方法,局部最优更新规则,以及外部种群档案剪枝规则中都嵌入了基于支配关系或距离因素的投票规则,以找到群体决策解,并且提高搜索效率。仿真结果表明该算法有效。     

Queueing analysis and optimal control of and systems

We first consider a finite-buffer single server queue where arrivals occur according to batch Markovian arrival process (BMAP). The server serves customers in batches of maximum size ‘b’ with a minimum threshold size ‘a’. The service time of each batch follows general distribution independent of each other as well as the arrival process. We obtain queue length distributions at various epochs such as, pre-arrival, arbitrary, departure, etc. Some important performance measures, like mean queue length, mean waiting time, probability of blocking, etc. have been obtained. Total expected cost function per unit time is also derived to determine the optimal value N^* of N at a minimum cost for given values of a and b. Secondly, we consider a finite-buffer single server queue where arrivals occur according to BMAP and service process in this case follows a non-renewal one, namely, Markovian service process (MSP). Server serves customers according to general bulk service rule as described above. We derive queue length distributions and important performance measures as above. Such queueing systems find applications in the performance analysis of communication, manufacturing and transportation systems.     

Hypothesis testing in rank-size rule regression

This note examines testing methods for Paretoness in the framework of rank-size rule regression. Rank-size rule regression describes a relationship found in the analysis of various topics such as city population, words in texts, scale of companies and so on. In terms of city population, it is basically an empirical rule that log?(_S(i))$\log ?(S_{(i)})$ is approximately a linear function of log?(i)$\log ?(i)$ where _S(i)$S_{(i)}$ is the number of population of i  th largest city in a country. This is closely related to the so-called Zipf’s law. It is known that this kind of empirical observation is found when the city population is a random variable following a Pareto distribution. Thus one may be willing to test if city size has a Pareto distribution or not. Rosen and Resnick [K.T. Rosen, M. Resnick, The size distribution of cities: an explanation of the Pareto law and primacy, Journal of Urban Economics 8 (1980), 165–186] and Soo [K.T. Soo, Zipf’s law for cities: a cross country investigation, Regional Science and Urban Economics (35) 2005, 239–263] regress log?(_S(i))$\log ?(S_{(i)})$ on log?(i)$\log ?(i)$ and log?²(i)${\log ?}^2(i)$ and test the null of Paretoness by standard t-test for the latter regressor. It is found that t-statistics take large values and the Paretoness is rejected in many countries. We study the statistical properties of the t-statistic and show that it explodes asymptotically, in fact, by simulation and thus the t-test does not provide a reasonable testing procedure. We propose an alternative test statistic which seems to be asymptotically normally distributed. We also propose a test with the null hypothesis that the city size distribution is Pareto with exponent unity, which is a modification of the F-test.     

Efficient single-pass frequent pattern mining using a prefix-tree

The FP-growth algorithm using the FP-tree has been widely studied for frequent pattern mining because it can dramatically improve performance compared to the candidate generation-and-test paradigm of Apriori. However, it still requires two database scans, which are not consistent with efficient data stream processing. In this paper, we present a novel tree structure, called CP-tree (compact pattern tree), that captures database information with one scan (insertion phase) and provides the same mining performance as the FP-growth method (restructuring phase). The CP-tree introduces the concept of dynamic tree restructuring to produce a highly compact frequency-descending tree structure at runtime. An efficient tree restructuring method, called the branch sorting method, that restructures a prefix-tree branch-by-branch, is also proposed in this paper. Moreover, the CP-tree provides full functionality for interactive and incremental mining. Extensive experimental results show that the CP-tree is efficient for frequent pattern mining, interactive, and incremental mining with a single database scan.     

Improved methods for extracting frequent itemsets from interim‐support trees

Mining association rules in relational databases is a significant computational task with lots of applications. A fundamental ingredient of this task is the discovery of sets of attributes (itemsets) whose frequency in the data exceeds some threshold value. In this paper we describe two algorithms for completing the calculation of frequent sets using a tree structure for storing partial supports, called interim‐support (IS) tree. The first of our algorithms (T‐Tree‐First (TTF)) uses a novel tree pruning technique, based on the notion of (fixed‐prefix) potential inclusion, which is specially designed for trees that are implemented using only two pointers per node. This allows to implement the IS tree in a space‐efficient manner. The second algorithm (P‐Tree‐First (PTF)) explores the idea of storing the frequent itemsets in a second tree structure, called the total support tree (T‐tree); the main innovation lies in the use of multiple pointers per node, which provides rapid access to the nodes of the T‐tree and makes it possible to design a new, usually faster, method for updating them. Experimental comparison shows that these techniques result in considerable speedup for both algorithms compared with earlier approaches that also use IS trees (Principles of Data Mining and Knowledge Discovery, Proceedings of the 5th European Conference, PKDD, 2001, Freiburg, September 2001 (Lecture Notes in Artificial Intelligence, vol. 2168). Springer: Berlin, Heidelberg, 54–66; Journal of Knowledge‐Based Syst. 2000; 13 :141–149). Further comparison between the two new algorithms, shows that the PTF is generally faster on instances with a large number of frequent itemsets, provided that they are relatively short, whereas TTF is more appropriate whenever there exist few or quite long frequent itemsets; in addition, TTF behaves well on instances in which the densities of the items of the database have a high variance. Copyright © 2008 John Wiley & Sons, Ltd.