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| 1 | CLS-Miner: efficient and effective closed high-utility itemset mining显示文摘High-utility itemset mining (HUIM) is a popular data mining task with applications in numerous domains. However, traditional HUIM algorithms often produce a very large set of high-utility itemsets (HUIs). As a result, analyzing HUIs can be very time consuming for users. Moreover, a large set of HUIs also makes HUIM algorithms less efficient in terms of execution time and memory consumption. To address this problem, closed high-utility itemsets (CHUIs), concise and lossless representations of all HUIs, were proposed recently. Although mining CHUIs is useful and desirable, it remains a computationally expensive task. This is because current algorithms often generate a huge number of candidate itemsets and are unable to prune the search space effectively. In this paper, we address these issues by proposing a novel algorithm called CLS-Miner. The proposed algorithm utilizes the utility-list structure to directly compute the utilities of itemsets without producing candidates. It also introduces three novel strategies to reduce the search space, namely chain-estimated utility co-occurrence pruning, lower branch pruning, and pruning by coverage. Moreover, an effective method for checking whether an itemset is a subset of another itemset is introduced to further reduce the time required for discovering CHUIs. To evaluate the performance of the proposed algorithm and its novel strategies, extensive experiments have been conducted on six benchmark datasets having various characteristics. Results show that the proposed strategies are highly efficient and effective, that the proposed CLS-Miner algorithm outperforms the current state-ofthe- art CHUD and CHUI-Miner algorithms, and that CLSMiner scales linearly. | Thu-Lan DAM Kenli LI Philippe FOURNIER-VIGER Quang-Huy DUONG | 2019 | Frontiers of Computer Science2019，13，2： | 9 |
| 2 | Communication contention in APN list scheduling algorithm显示文摘Task scheduling is an essential aspect of parallel process system. This NP-hard problem assumes fully connected homogeneous processors and ignores contention on the communication links. However, as arbitrary processor network (APN), communication contention has a strong influence on the execution time of a parallel application. This paper investigates the incorporation of contention awareness into task scheduling. The innovation is the idea of dynamically scheduling edges to links, for which we use the earliest finish communication time search algorithm based on shortest-path search method. The other novel idea proposed in this paper is scheduling priority based on recursive rank computation on heterogeneous arbitrary processor network. In the end, to reduce time complexity of algorithm, a parallel algorithm is proposed and speedup O(PPE) is achieved. The comparison study, based on both randomly generated graphs and the graphs of some real applications, shows that our scheduling algorithm significantly surpasses classic and static communication contention awareness algorithm, especially for high data transmission rate parallel application. | TANG XiaoYong LI KenLi PADUA Divid | 2009 | Science in China(Series F)2009，52，1： | 5 |
| 3 | 科学研究的第五范式——以智能驱动的材料设计为例显示文摘科学正在进入一个新时代——第五范式——它被认为是知识整合到不同领域的主要特征,是基于无所不在的机器学习系统的计算社区中智能驱动的工作。在此,我们通过在天河一号超级计算机系统上构建的催化材料专门设计的典型平台案例,生动地阐明了第五范式的本质,旨在促进第五范式在其他领域的培养。第五范式平台主要包括模型自动构建(原始数据提取)、指纹自动构建(神经网络特征选择)以及跨学科知识串联的重复迭代(“火山图”)。与分解一起进行的是对迭代中实现的体系结构的性能评估。通过讨论,第五范式的智能驱动平台可以极大地简化和改进研究中极其繁琐和具有挑战性的工作,并通过补偿机器学习中缺少样本和替代一些由于计算资源不足而导致的数值计算来实现数值计算与机器学习之间的相互反馈,从而加速探索过程。在数据驱动的学科中,跨学科专家的协同作用和对动态数据需求的急剧增长仍然是一个挑战。我们相信,对第五范式平台的一瞥可以为其在其他领域的应用铺平道路。 | Can Leng Zhuo Tang Yi-Ge Zhou Zean Tian Wei-Qing Huang Jie Liu Keqin Li Kenli Li | 2023 | Engineering2023，，5： | 2 |
| 4 | RTS-PGATS based approach for data-intensive scheduling in data grids显示文摘格子计算是计算机资源在的联合一泛泛地联合了,异构,并且地理上驱散的环境。格子数据是在格子计算使用的数据,它由大规模数据集中的应用程序组成,生产并且消费数据的巨大的数量,越过很多机器分布式。数据格子计算填写其各个要求可以各在不同资源上被复制的巨大的分布式的数据集合的独立任务的集合。减少应用程序的结束时间并且改进格子的性能,适当计算资源应该被选择执行这些任务和选择服务这些任务要求的文件的适当存储资源。这个问题能因此被分解为二亚问题:存储资源的选择和到计算资源的任务的赋值。这份报纸建议一个调度程序,它被分解为能在平行跑并且使用两平行禁忌搜索和一个平行基因算法的三部分。最后,建议算法被把它与另外的相关算法作比较评估,它指向最小化 makespan。模拟结果证明建议途径能是为安排大数据格子应用的一种好选择。 | Kenli LI Zhao TONG Dan LIU Teklay TESFAZGHI Xiangke LIAO | 2011 | Frontiers of Computer Science2011，5，4： | 2 |
| 5 | List scheduling with duplication for heterogeneous computing systems显示文摘 | Tang Xiaoyong Li Kenli Liao Guiping | 2010 | J Parallel Distrib Comput2010，70，4： | 1 |
| 6 | Reliability-aware scheduling strategy for heterogeneous distributed computing systems显示文摘 | XIAO Y T KENLI L RENFA L | 2010 | Journal of Parallel and Distributed Computing2010，70，9： | 1 |
| 7 | Effect of antiretroviral thera- py on the incidence of bacterial pneumonia in patients with advanced HIV infection 显示文摘 | Sullivan JH Moore RD Kenly JC | 2000 | Am J Respir Crit Care Med2000，162，1： | 1 |
| 8 | A MapReduce task schedu- ling algorithm for deadline constraints 显示文摘 | Tang Huo Zhou Junqing Li Kenli | 2013 | Cluster Computing2013，16，4： | 1 |
| 9 | Chemical reaction optimization with greedy strategy for the 0 - 1 knapsack prob- lem 显示文摘 | TUNG Khactruong LI Kenli XU Yuming | 2013 | Applied Soft Computing2013，13，4： | 1 |
| 10 | Scheduling scheme on heterogeneous computing systems using double molecular structure:based chemical reaction opti- mization显示文摘 | Yuming Xu Kenli Li Ligang He et al | 2013 | Journal of Parallel and Distributed Compu ring2013，73，9： | 1 |
| 11 | Reliability-aware scheduling strategy for heterogeneous distributed computing systems显示文摘 | Tang Xiaoyong Li Kenli Li Renfa | 2010 | Journal of Parallel and Distributed Computing2010，70，9： | 1 |
| 12 | Fast parallel molecular algorithms for DNA-based computation: Solving the elliptic curve discrete logarithm problem over GF(2^n) 显示文摘 | Li Kenli Zou Shuting Xu Jin | 2008 | Journal of Biomedicine and Biotechnology2008，，1： | 1 |
| 13 | A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues显示文摘 | Xu Yuming Li Kenli Hu Jingtong | 2014 | Information Science2014，270，： | 1 |
| 14 | Diagnosis of Multiple Sensor and Actuator Failures in Automotive Engines显示文摘 | Lin Kenli Shen Licheng | 1995 | IEEE Transactions on Vehicular Technology1995，44，4： | 1 |
| 15 | Convergence performance com- parison of quantum-inspired multi-objective evolutionary algo- rithms显示文摘 | Li Zhiyong Rudolph G Li Kenli | 2009 | Computers and Mathematics with Applications2009，57，： | 1 |
| 16 | Energy-Aware Scheduling with Uncertain Execution Time for Real-Time Systems显示文摘Energy-saving is extraordinary important for real-time systems. Dynamic voltage scaling(DVS) is an important technique to reduce the energy consumption of processors that support voltage scaling. It has been exploited extensively in task scheduling. However, many approaches take simple treatments and some of them even neglect the large voltage transition overheads. Although some strategies consider the penalty, frequency switching produces extra large time overhead and deadline misses occur frequently. In our paper, we propose an energy efficient soft real-time dynamic program scheme by using quantitative switching overhead and communication penalty for multitask scheduling with uncertain execution time. The experiments show that our approaches significantly outperform existing solutions both on simple-core and multi-core systems in terms of energy-saving. | ZHANG Longxin TONG Zhao ZHU Ningbo XIAO Zheng LI Kenli | 2017 | Chinese Journal of Electronics2017，26，1： | 1 |
| 17 | A MapReduce task scheduling algorithm for deadline constraints 显示文摘 | Huo Tang Junqing Zhou Kenli Li | 2013 | Cluster Computing2013，164，： | 1 |
| 18 | A MapReduce task scheduling algorithm for deadline constraints 显示文摘 | Zhuo Tang Junqing Zhou Kenli Li | 2013 | Cluster Computing2013，，： | 1 |
| 19 | A stochastic scheduling algorithm for precedence constrained tasks on Grid显示文摘 | Xiaoyong Tang Kenli Li Guiping Liao Kui Fang Fan Wu | 2011 | Future Generation Computer Systems2011，，8： | 1 |
| 20 | Reliability-aware scheduling strategy for heterogeneous distributed computing systems显示文摘 | Xiaoyong Tang Kenli Li Renfa Li Bharadwaj Veeravalli | 2010 | Journal of Parallel and Distributed Computing2010，，9： | 1 |
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