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International Conference on computer Supported Cooperative Work in Design

作者： Xiaowei Liu Wenhui Chen Mengmeng Sun Yali Si Zhen Chen School of Information Science and Engineering Yanshan University Qinhuangdao China School of Computer Science and Engineering Changshu Institute of Technology Changshu China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

With the popularity of the service-oriented development paradigm in the cloud era, numerous cloud APIs have been developed. The continuous proliferation of cloud APIs has submerged developers in a sea of options, bringing the need for cloud API recommendation techniques. Most existing cloud API recommendation methods focus on theoretical studies and neglect practical applications. As a result, these methods face several challenges, such as covering recommendation scenarios, generating real-time responses, and handling concurrent requests. In this paper, we propose and implement a practical cloud API complementary recommendation service for mashup creation. To address the above challenges, we first propose a cloud API complementary recommendation framework named FICR, which exploits feature interactions to mine implicit complementarity and models complementarity from the mashup side and the target cloud API side for scenario coverage. Then, we conduct performance optimization via precoding and batch size tuning to optimize FICR for real-time responses. Finally, we design a minimum-connection load balancing algorithm with resource early warning and build a distributed system for concurrent requests. Experiments conducted on real-world datasets show that FICR outperforms state-of-the-art baseline models in complementary recommendation scenarios, and demonstrate that the implemented service meets the real-time and concurrency requirements. The service will serve as a practical tool to help developers during mashup creation.

关键词： Concurrent computing Federated learning Mashups Precoding Load management Real-time systems Tuning

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Mining the important nodes of software based on complex networks

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ICIC Express Letters 2015年第12期9卷 3263-3268页

作者： Huang, Guoyan Zhang, Peng Li, Yanling Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave Qinhuangdao China

The main purpose of studying the software structure is considered to understand and recognize the structure easily by also taking into account the quality of software. In this paper, we define and analyze the node importance based on the invoking dependency relationships among the nodes to mine the influential nodes for the software. Firstly, we construct a directed network to denote the software execution process depending on the invoking relationships. Secondly, according to the information of the Dependency Node Set (DNS) of each function node, we define the importance for the node. Finally, we present the algorithm Measure the Importance of Node (MIN) to evaluate the importance of each node. Comparing the value of nodes by the algorithm Mining the top-K Nodes (MKN), we can obtain the most influential nodes in the software network. In addition, with experiments results, the method MKN is verified to be effective for measuring the importance of the function nodes accurately. © 2015 ICIC International.

关键词： Complex networks

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New construction of quaternary sequence with even period based on cyclotomic classes of order two

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ICIC Express Letters 2015年第7期9卷 1959-1964页

作者： Jia, Yanguo Shi, Yan Duan, Xiaobei Shen, Xiumin School of Information Science and Engineering Yanshan University No. 438 West Hebei Street Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Heibei Province No. 438 West Hebei Street Qinhuangdao China

In this paper, we present a new method for constructing quaternary sequence with even period 2f based on cyclotomic classes of order two. Under the premise of v = 2f +1, we construct two binary sequences with period 2f. Then we can construct a new quaternary sequence from those two binary sequences by using the reverse Gray Mapping. The distribution of autocorrelation function of the proposed quaternary sequence is also derived, which is decided by the parity of f. © 2015, ISSN 1881-803X.

关键词： Binary sequences

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Mining software behavior pattern from software execution trace

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ICIC Express Letters, Part B: Applications 2015年第12期6卷 3367-3372页

作者： Ren, Jiadong Wu, Hongfei Yin, Tengteng Li, Yanling Liu, Jiaxin Dong, Jun College of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology System Integration of Hebei Province No. 438 Hebei Avenue Qinhuangdao066004 China

A software execution trace can be viewed as a series of events. An event may correspond to the execution of a basic block, the invocation of a class or a method. These traces imply important unique characteristics of software behaviors. In this paper, a novel approach to mine representative software behavior patterns is proposed. First, we give an exact definition of Common Closed Ordered Iterative Pattern (CCOIP). The pattern may occur many times not only within a single trace but also across multiple traces. Then, an efficient algorithm called CCOIP-Miner is proposed to mine CCOIP. The mined CCOIPs are regarded as representative software behavior patterns. Our experiment results show the efficiency of algorithm CCOIP-Miner. © 2015, ICIC Express Letters Office. All rights reserved.

关键词： Miners

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Research on community detection algorithm based on modularity maximum

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ICIC Express Letters 2016年第12期10卷 2995-3003页

作者： Chen, Jing Wan, Yun College of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Avenue Qinhuangdao066004 China

It is well known that the drawbacks of label propagation algorithm are high randomness, weak robustness and easy to form monster community. Many improved methods are proposed constantly in order to avoid these problems. However, the related label propagation algorithm is seldom concerned with the stability of community structure and the results of community detection. In order to obtain the high value communities, modularity and community structure are involved in detecting communities. In this paper, the algorithm CDMMCS (Community Detection based on Modularity Maximum and Community Structure) is proposed. The main idea is based on label propagation, but CDMMCS begins with some small communities, and the process of label updating is in consideration of the modularity maximum. When the label stops propagating, the communities with the same label are merged. Check the community structure of merged communities, and perform different operations according to different community structures. Experiments show that CDMMCS successfully detects communities with higher modularity values than LPA (label Propagation Algorithm) and LPAm+ in some realworld networks. And the running time of CDMMCS is less than LPAm+. © 2016 ICIC International.

关键词： Population dynamics

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An improved algorithm for detecting community structure based on node similarity

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Journal of Computational Information systems 2014年第9期10卷 3805-3813页

作者： Guo, Jingfeng Wei, Aiying Lv, Jiaguo Liu, Zhen College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China College of Information Science and Engineering Zaozhuang University Zaozhuang 277100 China

Detecting community structure based on node similarity cost lower time complexity, but they ignore the indirect relationships of nodes. We proposed an improved algorithm for detecting community structure based on node similarity (AINS). The algorithm presents a neighbor subgraph model based on akincore node pair, considering the direct and indirect relations between nodes. It introduced node indirect similarity to solve the problem which only pay attention to direct relationships, ensuring that the results meet the common definition of community structure (the number of edges between community is greater than that within community). The experimental results show that the AINS algorithm can obtain better community classification result effectively. © 2014 Binary Information Press.

关键词： Information systems

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The effects of DHPG stimulation on spikes and theta frequency oscillations and spike-theta oscillation relations in rat MSDB slice

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Journal of Convergence Information technology 2012年第17期7卷 442-449页

作者： Wen, Dong Ouyang, Gaoxiang Peng, Ce Li, Xiaoli Lu, Chengbiao Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Yanshan University Qinhuangdao Hebei China Institue of Electrical Engineering Yanshan University Qinhuangdao Hebei China National Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing 100088 China

Neuronal oscillations in the theta frequency range and spikes have been reported in many cortical areas in the information processing, but the role of spikes play in cortical processing remains unclear. The aim of this study was to examine the role of DHPG in the generation of oscillatory field activity at theta frequency in the medical septal diagonal band of Broca (MSDB) slice prepared from rat brain, and to determine the phase relationship between spikes and theta oscillations. The DHPG induced large amplitude field population spiking activity, which is correlated linearly with the field theta oscillations. The relationship between timing of spikes and the phase of theta oscillation was determined by an analysis of circular statistics. Further analysis with Rayleigh test revealed that the relationship of phase-locking between spikes and theta rhythm is of statistical significance. These data demonstrate that DHPG-sensitive neuronal networks within medial septum are able to generate theta oscillations which are modulated by large amplitude population spikes and phase-locking of spikes to the theta rhythm suggest the role of memory enhancement in the presence of mGluR1 activation.

关键词： Rats

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A novel algorithm for outlier mining in the internet of things

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ICIC Express Letters 2013年第1期7卷 215-219页

作者： Chen, Wei Liu, Yongshan Zhang, Yang College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province No. 438 Hebei Ave. Qinhuangdao 066004 China

Most of the traditional outlier mining algorithms are not suitable for high dimensional datasets. However, the dimensionality of the dataset in the field of the Internet of Things is high. Therefore, Hypergraph-based Outlier Mining (HOM) algorithm is proposed to solve the problem. Two different hypergraph models are constructed in the HOM algorithm. One is itemset hypergraph. One-itemset in transaction database is itemset hypergraph's vertices, and the transactions are itemset hypergraph's hyperedges. The other one is transaction hypergraph. The transactions are its vertices, and frequent itemsets are the hyperedges. The outliers are found by hypergraph partitioning. Experiments show that HOM algorithm can effectively find the outliers in high dimensional space. ©2013 ICIC International.

关键词： Statistics

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Performance analysis of the centralized channel allocation strategy in cognitive radio networks

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ICIC Express Letters 2013年第7期7卷 2189-2196页

作者： Dai, Yu Jin, Shunfu Meng, Chao College of Information Science and Engineering Yanshan University No. 438 Hebei Ave Qinhuangdao 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave Qinhuangdao 066004 China

Based on the centralized channel allocation strategy in the Cognitive Radio Networks, considering the opportunistic channel access for Secondary Users, a discretetime queueing model with a general transmission time and possible transmission interruption is established. By using the method of an embedded Markov chain, the system model is analyzed in steady state, and the performance metrics in terms of the average latency, the throughput for the Secondary User, the channel switching ratio and the channel utilization are given accordingly. Analysis results and simulation experiments are provided to investigate the influence of the traffic load for the Secondary User and the arrival rate for the Primary User packets on the system performance. © 2013 ICIC International.

关键词： Cognitive radio

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A weighted clustering algorithm based on user’ access sequence similarity

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ICIC Express Letters 2016年第10期10卷 2363-2370页

作者： Li, Weina Han, Gaowei Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave. Qinhuangdao066004 China

Consider traditional clustering algorithms seldom had a research on users’ visit behavior and content, and they cannot cluster users with similar visit behavior into a community easily. Behavior of user cannot cluster users with similar visit behavior i also reflect usery. Behavior Therefore, setting about the log of user’s access behavior, in view of visitor volume, sequences of accessing keywords and time interval between keywords, a weighted clustering algorithm based on sequence similarity which is called K-Similar is put forward. Starting from behavior of user’s access to document, users are clustered, and important users are divided into a community. Then, literature needs of users in the same cluster are mined. This algorithm has been verified in users users are log data in CNKI, available for academic publishing. Experimental results show that K-Similar is more efficient in efficiency and accuracy. It can obtain more interesting user communities and show academic publishing demand of special users. © 2016 ICIC International.

关键词： Clustering algorithms

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