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New friend recommendation with user interest and socialization

Journal of Information and Computational Science 2015年第11期12卷 4253-4262页

作者： Huang, Guoyan Chang, Yixin Li, Yakun College of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

Friend recommendation is popular in social site to help people make new friends and expand their social networks. However, the conventional friend recommendation method is low accuracy for the sparsity of data and cold start. To solve this problem, we propose a new personalized recommendation method with user interest and socialization. This approach incorporating user interest and social information mainly leverages both user-based collaborative filtering method and user topological structure in social networks. Firstly, user interest degree can be obtained to identify the user preferences. Secondly, get the new optimized similarity degree and the target user's nearest neighbor by using social collaborative filtering algorithm. In the end, the final recommendation set of user can be acquired from the highest predicted rating of the candidate collection. The experiments indicate that this proposed method can enhance the Effectiveness and accuracy of recommendation compared with the traditional friend recommendation algorithm. ©, 2015, Binary Information Press. All right reserved.

关键词： Collaborative filtering

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A novel approach to efficiently mine structural patterns from software execution sequence

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Journal of Computational Information systems 2015年第3期11卷 1109-1119页

作者： Huang, Guoyan Zhang, Bing Ren, Rong Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

Analyzing structure of a software system is not sufficient for understanding its functionality. Certain characteristics of software are often hidden in its structure and can only be discovered when the various execution sequence of the software are identified. Analysis of execution sequence, therefore, becomes an indispensable aid in software comprehension. In this paper, a novel approach to efficiently mine structural patterns from software execution sequence is proposed. First, software execution traces are modeled as sequential patterns. Due to loops, patterns can occur multiple times within a trace, which leads to high cost of time and super complexity of the research. Then, an algorithm is designed to eliminate repetitive patterns (ERP) in software and software sequential pattern mining (SSPM) algorithm is presented to divide software unique sequential patterns into different patterns in order to mine structural characteristics of the software. At last, by the comparative analysis of similarity between different pattern collections, it draws the conclusion that software system can be compartmentalized into n fixed patterns. Experimental results also prove the conclusion well. ©, 2015, Binary Information Press. All right reserved.

关键词： computer software

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Commodity dynamic pricing and inventory joint decision-making model based on specific power demand function

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Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia 2016年第4期39卷 74-81页

作者： Sun, Dejie Liu, Wenyuan Zhang, Jie School of Information Science and Engineering Yanshan University Qinhuangdao Hebei066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao Hebei066004 China

Dynamic pricing and inventory play a respective role. The purpose of inventory is to try best to maintain an even production speed and efficiently ease supply-and-demand contradiction during the production process and among enterprises in the supply chain. However, dynamic pricing aims at maximizing revenues by setting commodities or services at different price levels according to diversified demands of consumers and different commodity or service price evaluation by consumers in different periods. Therefore, it is important for enterprises to optimize their dynamic pricing strategies and commodity inventory so as to maximize value of researches. However, demands for tangible commodities are uncertain. Generally speaking, the commodity demand volume should first be confirmed before any specific analysis. Therefore, this paper focuses on introducing the commodity demand function and relevant factors influencing the commodity demand volume. The utility function describing consumers' demands for a single commodity is analyzed. The specific power demand function model based on utility maximization is built through the utility function. At last, we conduct an in-depth analysis and simulation of the model.

关键词： Economics

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Kainate induced gamma oscillations and spike-gamma relationship analysis

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Advances in Information Sciences and Service Sciences 2012年第21期4卷 606-612页

作者： Wen, Dong Peng, Ce Li, Xiaoli Lu, Chengbiao The Key Laboratory for Computer Virtual Technology System Integration of HeBei Province Yanshan University Qinhuangdao Hebei 066004 China Institue of Electrical Engineering Yanshan University Qinhuangdao Hebei 066004 China

Neuronal oscillations in the gamma 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 kainate in the generation of oscillatory field activity at gamma frequency in the hippocampal slice prepared from rat brain, and to determine the phase relationship between spikes and gamma oscillations. The kainate induced large amplitude field population spiking activity, which is correlated linearly with the field gamma oscillations. The relationship between timing of spikes and the phase of gamma oscillation was determined by an analysis of circular statistics. Further analysis with Rayleigh test revealed that the relationship of phase-locking between spikes and gamma rhythm is of statistical significance. These data demonstrate that kainate sensitive neuronal networks within hippocampus are able to generate gamma oscillations which are modulated by large amplitude population spikes and phase-locking of spikes to the gamma rhythm suggest the role of memory enhancement in the presence of Kainate receptor activation.

关键词： Locks (fasteners)

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Real-time simulation of action-driven 3D subtle facial expressions

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Journal of Computational Information systems 2014年第5期10卷 2137-2144页

作者： Tang, Yong Liang, Haiyan Guo, Dan Lv, Mengya Zhao, Jing College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

While the large-scale deformations such as the Laplacian deformation method could not synthesize new expressional details, this paper proposes a method for simulating different subtle facial expressions based on the Kinect acquisition system and the facial expressional reconstruction technique. Firstly, we generate the coarse skin textures with pore details and those normal maps. Secondly, we use blending wrinkle maps to render animated details on a human face based on a GPU shader program. Finnaly, according to the action units captured by the Kinect, we calculate the dynamic texture mapping and the weight of wrinkles, and apply the wrinkles function to simulate the motion of wrinkles. Experimental results show that our method can generate facial details in real time. The method suits the fields such as digital entertainment and video conferences. © 2014 Binary Information Press.

关键词： Blending

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Mining weighted closed sequential patterns by memory indexing

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2012年第19期6卷 432-440页

作者： Ren, Jiadong Li, Shuo Dong, Jun College of Information Science and Engineering Yanshan University Qinhuangdao Hebei 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

There exist two major problems in weighted closed sequential patterns mining. The first is that only the weights of items are considered and they ignore the time-interval information of data elements during the mining process;the second is that the existing weighted closed sequential pattern mining algorithms need to scan the sequence database many times or to construct numerous intermediate databases. To address these problems, we propose a memory-based algorithm, MIWCSpan (Memory Indexing for Weighted Closed Sequential pattern mining), for weighted closed sequential pattern mining. In the algorithm, we define a novel sequence weighting approach to find more interesting sequential patterns. Both the weight of sequence items and the time-interval of the data elements are considered in this approach. Moreover, an improved index set based on time-interval, p-iidx, is defined. The structure is a set of triples which store the pointer pointing to the sequence containing p, the time-interval of p in the sequence and the position where p occurs. In the mining process, MIWCSpan first scans the sequence database to read the database into memory. Then it adopts the find-then-index technique recursively to find the items which can constitute a weighted closed sequential pattern and construct p-iidx for the possible weighted closed sequential pattern. At last, the algorithm uses the close-detecting to mine the weighted closed sequential patterns efficiently. The experimental results show that MIWCSpan is better on running time, and it has good scalability.

关键词： Database systems

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Data stream clustering algorithm based on spatial directed graph

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Advances in Information Sciences and Service Sciences 2012年第20期4卷 241-249页

作者： Ren, Jiadong Yuan, Xuemei Dong, Jun College of Information Science and Engineering Yanshan University Qinhuangdao Hebei 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

Recently, the grid-density based clustering has become one of the major issues among all of the clustering approaches, it has special advantages over other clustering algorithms, such as less computation and the ability of clustering with arbitrarily shape, which are particularly useful for the data stream clustering. This paper defines a spatial directed graph named Grid-Based Graph (GBG) to store the non-empty grids in data space, and proposes a data stream clustering algorithm based on spatial directed graph GBGSClu (Grid-Based Graph Stream Clustering). GBG graph composes of vertices and directed edges, if a vertex A has a neighboring dense vertex B, and then there is a directed edge from vertex B to A in GBG. The algorithm maps the data stream into the non-empty vertices online, updates the vertices' feature vectors with the arriving of data stream, deletes the sparse vertices every gap time, generates GBG graph when the clustering quest coming and finally clusters on the current structure. The eventual clustering results can be obtained by only checking the vertices' in-degree which can reduce the computation needed in clustering. The validity and efficiency of GBGSClu algorithm have been tested and verified by clustering on real and synthetic datasets.

关键词： Directed graphs

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Subspace clustering based on finding effective spaces

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2012年第22期6卷 580-589页

作者： Ren, Jiadong Liu, Zhigang Dong, Jun College of Information Science and Engineering Yanshan University Qinhuangdao Hebei 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

In high-dimensional data space, because the data is sparse inherently, clusters tend to exist in different subspaces, which makes the traditional methods no longer suitable for use. In this paper, we present SCFES, a subspace clustering algorithm based on finding effective spaces. First, we define the effective dimension. By calculating relative entropy we remove redundancy dimensions which affect clustering accuracy. Second, according to the data distribution in the effective dimensions, we get the effective intervals through merging adjacent intervals. The effective space is composed of effective intervals. Third, we extend the density estimator based on undirected acyclic connected graph by using weight so as to estimate the expectation of existing clusters in the space, at the same time combine it with the monotonicity of the clustering criterion mentioned in the CLIQUE algorithm to prune candidates. Consequently we get the effective spaces. Finally, we adopt the structure of sibling tree to store all the effective spaces and use DBSCAN algorithm based on density to generate maximal subspace clusters in some effective spaces. Experimental results show that SCFES effectively finds arbitrarily shaped and positioned clusters in different subspaces. Meanwhile SCFES has better clustering quality and scalability.

关键词： Clustering algorithms

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IMSPMIS-Stream: incremental mining of top-k short sequential pattern over multiple item set streams

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Journal of Computational Information systems 2014年第6期10卷 2305-2312页

作者： Hao, Xiaobing Han, Gaowei Chen, Yuping Wang, Peilong Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

Many previous algorithms in data streams are about single stream, which can only process single items. The algorithms about data streams are always extended by sequential pattern algorithms about static database, they can't satisfy the requirement of scanning streams only once and online mining. Moreover, top-k short sequential pattern hasn't been studied yet. Therefore, IMSPMIS-Stream algorithm is proposed to mine online multiple streams with the single scan by the incremental method in this paper. The streams are continuous transactions, which is also called item set streams. Several streams are mined interactively based on sliding windows at the same time. An approach to count the support of every sub item set is designed to get the support during one scan. The short sequential pattern is deffned, whose item sets are shorter than all the item sets with the same occurring time. When the arrival transactions reach to the capacity of the window, sequential patterns will be output by combining top-k short item sets. The experiments show that the IMSPMIS-Stream algorithm overcomes the memory limitation and its execution time is reduced compared with some previous algorithms under the same conditions. Copyright © 2014 Binary Information Press.

关键词： Information systems

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Performance evaluation of an enhanced Ethernet energy saving mechanism in IEEE 802.3az

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Journal of Information and Computational Science 2014年第5期11卷 1605-1613页

作者： Zhi, Shengyang Jin, Shunfu Meng, Chao 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

In order to reduce the energy consumption and improve the response performance, by introducing the strategies of sleep-delay, pre-awake and split timing to IEEE 802.3az, an enhanced Ethernet energy saving mechanism is proposed. Considering the digital nature of modern communications, a discrete-time queueing model with multiple-vacation and N-strategy is built. With the method of an embedded Markov chain, we evaluate the energy saving efficiency of the system and the response performance of the data frames mathematically. Numerical experiments and simulation results show that, in the enhanced Ethernet energy saving mechanism, the average packet latency is reduced, while the energy saving ratio is satisfactory. © 2014 by Binary Information Press.

关键词： Energy conservation

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