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Incremental Influence Maximization for Dynamic Social Networks

Incremental Influence Maximization for Dynamic Social Networ...

The Third International Conference of Pioneering Computer Scientists, Engineers and Educators,ICPCSEE 2017(originally ICYCSEE)

作者： Yake Wang Jinghua Zhu Qian Ming School of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province

Influence maximization is one fundamental and important problem to identify a set of most influential individuals to develop effective viral marketing strategies in social network. Most existing studies mainly focus on designing efficient algorithms or heuristics to find Top-K influential individuals for static network. However, when the network is evolving over time, the static algorithms have to be re-executed which will incur tremendous execution *** this paper, an incremental algorithm DIM is proposed which can efficiently identify the Top-K influential individuals in dynamic social network based on the previous information instead of calculating from scratch. DIM is designed for Linear Threshold Model and it consists of two phases: initial seeding and seeds updating. In order to further reduce the running time, two pruning strategies are designed for the seeds updating phase. We carried out extensive experiments on real dynamic social network and the experimental results demonstrate that our algorithms could achieve good performance in terms of influence spread and significantly outperform those traditional static algorithms with respect to running time.

关键词： Influence maximization Dynamic social network Linear threshold model Pruning strategy

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Influence Equilibrium Problem Research Based on Common Interests in Mobile Social Network 12

Influence Equilibrium Problem Research Based on Common Inter...

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12th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2016

作者： Li, Jinbao Han, Yue Zhu, Jinghua School of Computer Science and Technology Heilongjiang University China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9781509056965

Influence maximization refers to the number of influenced nodes reach to maximum by finding a set of seed nodes in social network. Due to peoples' excessive concentration of attention, sometimes, negative effects will appear during the influence propagation. However, the negative effects on influence propagation are not involved in the existing research work. In this paper, we consider the influence equilibrium problem in mobile social network. The goal of influence equilibrium is to balance the influential range of different kinds of seed sets through the way of node scheduling. Our goal is to reduce the negative effects by transforming the status of influence from excessive concentration to relatively balanced. There are two main challenges: (1) which nodes should be scheduled in mobile social network in order to achieve a balanced effect. (2) how to schedule the nodes. To address the two challenges, we estimate the randomness of nodes and then schedule the nodes which have high randomness. The entropy-based random walk select balance algorithm(RSB) is proposed in this paper. To achieve the balanced effect, random walk procedure is adopted to choose the sets that can receive the scheduled nodes during the scheduling phase. However, new imbalance may arise during this procedure. Thus, the entropy-based max-min balance algorithm(MMB) is proposed to deal with the new imbalance caused by RSB algorithm. Theoretical analysis and experimental results show that the RSB and MMB algorithm can balance the influence range and MMB performs better than RSB. © 2016 IEEE.

关键词： Entropy

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Using gaussian mixture model to fix errors in SFS approach based on propagation 2nd

Using gaussian mixture model to fix errors in SFS approach b...

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2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016

作者： Huang, Wenmin Ma, Jiquan Zhang, Enbin College of Computer Science and Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9789811020520

A new Gaussian mixture model is used to improve the quality of propagation method for SFS in this paper. The improved algorithm can overcome most difficulties of propagation SFS method including slow convergence, interdependence of propagation nodes and error accumulation. To slow convergence and interdependence of propagation nodes, stable propagation source and integration path are used to make sure that the reconstruction work of each pixel in the image is independent. A Gaussian mixture model based on prior conditions is proposed to fix the error of integration. Good result has been achieved in the experiment for Lambert composite image of the front illumination. © Springer Science+Business Media Singapore 2016.

关键词： Errors

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CTS: Combine temporal influence and spatial influence for time-aware POI recommendation 2nd

CTS: Combine temporal influence and spatial influence for ti...

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2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016

作者： Zhang, Hanbing Yang, Yan Zhang, Zhaogong School of Computer Science and Technology Heilongjiang University Harbin150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin150080 China

ISBN: (纸本)9789811020520

As location-based social network (LBSN) services become more popular in people’s lives, Point of Interest (POI) recommendation has become an important research *** recommendation is to recommend places where users have not visited before. There are two problems in POI recommendation: sparsity and precision. Most users only check-in a few POIs in an LBSN. To tackle the sparse problem in a certain extent, we compute the similarity between the check-in datasets of different times. For the precision problem, we incorporate temporal information and geographical information. The temporal information will influence how the user chooses and allow the user to visit different distance point on different day. The geographical information is also used as a control for points which are too far away from the user’s check-in data. Our experimental results on real life LBSN datasets show that the proposed approach outperforms the other POI recommendation methods substantially. © Springer Science+Business Media Singapore 2016.

关键词： Collaborative filtering

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CTS: Combine Temporal Influence and Spatial Influence for Time-Aware POI Recommendation

CTS: Combine Temporal Influence and Spatial Influence for Ti...

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The Second International Conference of Young Computer Scientists, Engineers and Educators,ICYCSEE 2016

作者： Hanbing Zhang Yan Yang Zhaogong Zhang School of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province

As location-based social network(LBSN) services become more popular in people's lives, Point of Interest(POI) recommendation has become an important research *** recommendation is to recommend places where users have not visited before. There are two problems in POI recommendation:sparsity and precision. Most users only check-in a few POIs in an LBSN. To tackle the sparse problem in a certain extent, we compute the similarity between the check-in datasets of different times. For the precision problem, we incorporate temporal information and geographical information. The temporal information will influence how the user chooses and allow the user to visit different distance point on different day. The geographical information is also used as a control for points which are too far away from the user's check-in *** experimental results on real life LBSN datasets show that the proposed approach outperforms the other POI recommendation methods substantially.

关键词： Recommendation Point-of-interest Location-based social network Collaborative filtering Spatio-temporal

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Using Gaussian Mixture Model to Fix Errors in SFS Approach Based on Propagation

Using Gaussian Mixture Model to Fix Errors in SFS Approach B...

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The Second International Conference of Young Computer Scientists, Engineers and Educators,ICYCSEE 2016

作者： Wenmin Huang Jiquan Ma Enbin Zhang College of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province

A new Gaussian mixture model is used to improve the quality of propagation method for SFS in this paper. The improved algorithm can overcome most difficulties of propagation SFS method including slow convergence, inter-dependence of propagation nodes and error accumulation. To slow convergence and interdependence of propagation nodes, stable propagation source and inte-gration path are used to make sure that the reconstruction work of each pixel in the image is independent. A Gaussian mixture model based on prior conditions is proposed to fix the error of integration. Good result has been achieved in the experiment for Lambert composite image of the front illumination.

关键词： Shape from shading Propagation method Silhouette Gaussian mixture model Surface reconstruction

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Tracking Nodes Selection Algorithm Based on Voronoi Structure in Sensor Networks

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Ruan Jian Xue Bao/Journal of Software 2017年 28卷 30-38页

作者： Ren, Qian-Qian Li, Jin-Bao Sun, Bei-Bei Key Laboratory of Database and Parallel Computing of Heilongjiang Province Heilongjiang University Harbin150080 China Key Laboratory of Electronic Engineering Colleges of Heilongjiang Province Heilongjiang University Harbin150080 China School of Computer Science and Technology Heilongjiang University Harbin150080 China

Energy saving and the tracking performance are two important issues in moving target tracking. This paper presents a Voronoi structure-based nodes selection algorithm, which constructs a network model based on the property of Voronoi, and selects sensor nodes which are more close to the target to participate in tracking. This paper also presents a nodes scheduling mechanism, which minimizes the number of awaking nodes with tracking quality guarantee. Finally, a set of simulation experiments are made to analyze the effects of various parameters on the network performance. Experimental results show the excellent performance of the proposed algorithm in terms of energy saving and tracking quality. © Copyright 2017, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Target tracking

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Data Dissemination Protocols Based on Opportunistic Sharing for Data Offloading in Mobile Social Networks

Data Dissemination Protocols Based on Opportunistic Sharing ...

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International Conference on parallel and Distributed Systems (ICPADS)

作者： Na Jiang Longjiang Guo Jinbao Li Meirui Ren Sisi Cheng Xiaodan Guo School of Computer Science and Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing Heilongjiang China

ISBN: (纸本)9781509053827

Due to the increasing popularity of smart mobile devices, the amount of mobile data communications has led to explosive growth of data traffic in cellular networks. Cellular networks have to face the challenge of huge communication traffic. Offloading data traffic through opportunistic communication among smart mobile devices is a promising solution to partially solve this problem since there is almost no monetary cost for it. Large amount of smart mobile devices can communicate each other using Bluetooth or WIFI Direct in short communication range and they can form an opportunistic mobile social network. The opportunistic communications among smart mobile devices can effectively reduce the amount of cellular data traffic. However, mobile users take a long time to obtain useful data. In order to reduce data communication latency, this paper proposes three data dissemination protocols named RRDP(Request-Reply Dissemination Protocol), RDP(Random Dissemination Protocol) and LDP(LRU Dissemination Protocol) respectively. The three proposed protocols are based on opportunistic sharing policy. Extensive NS-2 simulation results show that (1) on the campus situation, the user's access delay of RDP is 56.4% less than the RRDP and LDP is 44.8% less than RRDP. (2) in the vehicular environment, the user's access delay of RDP is 32.5% less than the RRDP and LDP is 28.1% less than RRDP. RDP is the best protocol.

关键词： Protocols Mobile nodes Data dissemination Cellular networks Delays

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Influence Equilibrium Problem Research Based on Common Interests in Mobile Social Network

Influence Equilibrium Problem Research Based on Common Inter...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Jinbao Li Yue Han Jinghua Zhu School of computer Science and technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongj iang Province Harbin China

ISBN: (纸本)9781509056972

Influence maximization refers to the number of influenced nodes reach to maximum by finding a set of seed nodes in social network. Due to peoples' excessive concentration of attention, sometimes, negative effects will appear during the influence propagation. However, the negative effects on influence propagation are not involved in the existing research work. In this paper, we consider the influence equilibrium problem in mobile social network. The goal of influence equilibrium is to balance the influential range of different kinds of seed sets through the way of node scheduling. Our goal is to reduce the negative effects by transforming the status of influence from excessive concentration to relatively balanced. There are two main challenges: (1) which nodes should be scheduled in mobile social network in order to achieve a balanced effect. (2) how to schedule the nodes. To address the two challenges, we estimate the randomness of nodes and then schedule the nodes which have high randomness. The entropy-based random walk select balance algorithm(RS_B) is proposed in this paper. To achieve the balanced effect, random walk procedure is adopted to choose the sets that can receive the scheduled nodes during the scheduling phase. However, new imbalance may arise during this procedure. Thus, the entropy-based max-min balance algorithm(MM_B) is proposed to deal with the new imbalance caused by RS_B algorithm. Theoretical analysis and experimental results show that the RS_B and MM_B algorithm can balance the influence range and MM_B performs better than RS_B.

关键词： Social network services Mobile communication Mobile computing Minimization Silicon Probability Software

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Research on Linkage Disequilibrium Method Based on OpenMP

Research on Linkage Disequilibrium Method Based on OpenMP

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International Conference on Information Science and Control Engineering (ICISCE)

作者： Jun Lu Jun Li Ruiqing Jing Qiong Wang Cheng Chang Jiaxing Guo College of Computer Science and Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9781509025367

Linkage disequilibrium method is applied for the research on inferring population genetics, LD mapping, haploid type diversity analysis and so on. Soybean genotypes are adopted as the data source and linkage disequilibrium parallel algorithm is implemented by OpenMP technology. In this algorithm, single nucleotide polymorphism sites are divided by using sliding windows into groups, adjacent sites allele in a window of each chromosome are parallel calculated and store the LD results. According to the experimental data, the serial and parallel algorithms are compared and analyzed. The conclusion shows that the OpenMP parallel technology can effectively improve the efficiency of linkage disequilibrium analysis method. It is a realistic significance for processing massive biological information data.

关键词： Biological cells Couplings Genetics Instruction sets Sociology Statistics parallel algorithms

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