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检索条件"机构=The Key Laboratory of Database and Parallel Computing"

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Quick-merge sort algorithm based on Multi-core linux

Quick-merge sort algorithm based on Multi-core linux

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International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Yong Liu Yan Yang School of Computer Science and Technology Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9781479925667

Sorting a list of input numbers is one of the most fundamental problems in the field of computer science. This paper presents an efficient implementation and detailed analysis of quick sort algorithm called QM-sort on Multi-core CPU architectures. Our QM-sort has two stages. The first stage is making blocks sorted, and the second stage is merging the sorted blocks. At the first stage, we propose a parallel quick sort algorithm named BPQsort. The run time of BPQsort achieves 40%-50% better than Qsort (STL), so we make blocks sorted more efficient. On the other hand, our algorithm can read file in parallel, thus reduce the time of reading file from disk. At the second stage, our parallel merge algorithm can operate the data on consecutive memory. Thus we avoid the expensive unaligned load/store operations, thus make our merge algorithm faster. At last, the run time of QM-sort is 10%-15% better than quick sort based on OpenMP.

关键词： Linux Instruction sets Hardware Algorithm design and analysis

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Negative Influence Maximization in Social Networks

Negative Influence Maximization in Social Networks

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2018国际计算机前沿大会（原国际青年计算机大会）

作者： Jinghua Zhu Bochong Li Yuekai Zhang Yaqiong Li School of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province

Influence maximization is one of the key research problems in social networks due to its wide applications like spread of ideas and viral marketing of products. Most of the existing work focus on social networks containing only positive relationships（e.g. friend or trust） between users, but in reality social networks containing both positive and negative relationships（e.g. foe or distrust）. Ignoring the negative relations may lead to over-estimation of positive influence in practical applications. Thus, in this paper, we study influence maximization problem with negative effects（NIM）. To address the NIM problem, we use the polarity Independent Cascade（IC-P） diffusion model which extends the standard Independent Cascade（IC） model with negative *** we propose the positive influence maximization algorithm（PIM） and negative influence maximization（NIM） problem. We prove that influence function of the NIM problem is monotonic and submodular, so we propose a CELF based algorithm（CELFIM） to solve it. Experiments results show that our algorithm has matching influence spread compared with greedy algorithm and achieves several orders of magnitude time improvement.

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An Incremental Partitioning Graph Similarity Search Based on Tree Structure Index

An Incremental Partitioning Graph Similarity Search Based on...

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2020国际计算机前沿大会

作者： Yuhang Li Yan Yang Yingli Zhong School of Computer Science Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province

Graph similarity search is a common operation of graph database,and graph editing distance constraint is the most common similarity measure to solve graph similarity search problem. However, accurate calculation of graph editing distance is proved to be NP hard, and the filter and verification framework are adopted in current method. In this paper, a dictionary tree based clustering index structure is proposed to reduce the cost of candidate graph, and is verified in the filtering stage. An efficient incremental partition algorithm was designed. By calculating the distance between query graph and candidate graph partition, the filtering effect was further enhanced. Experiments on real large graph datasets show that the performance of this algorithm is significantly better than that of the existing algorithms.

关键词： Graphsimilaritysearch Similaritysearch Graphpartition

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PSHCAR: A Position-Irrelevant Scene-Aware Human Complex Activities Recognizing Algorithm on Mobile Phones

PSHCAR: A Position-Irrelevant Scene-Aware Human Complex Acti...

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2018国际计算机前沿大会（原国际青年计算机大会）

作者： Boxuan Jia Jinbao Li Hui Xu School of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province

Recognizing human complex activities has become an essential topic in pervasive computing research area. With the growing popularity of mobile phones, more and more studies have been dedicated to identifying human complex activities using mobile phones in recent years. However, previous works often restrain the position and orientation of cell phones which limit the applicability of their methods. To overcome this limitation, we propose a novel position-irrelevant activities identification method named PSHCAR, which efficiently utilize information from multiple sensors on smartphones. Moreover,besides commonly-used features such as accelerometer and gyroscope,PSHCAR also employ the knowledge about scenes of activities, which is helpful but ignored by previous works, to identify complex activities of mobile phone users. Comparative experiments show that our method performs better than several strong baselines on the task of human complex activities recognition. In conclusion, our method achieves state-of-the-art performance without any limitation on position or orientation of mobile phones.

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Research on parallel F-statistics estimation algorithm based on OpenMP

Research on Parallel F-statistics estimation algorithm based...

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2015 IEEE Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2015)

作者： Ruiqing Jing Jun Lu Jun Li Kang Wan Haoyu Zhang College of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province

ISBN: (纸本)9781479919819

The genetic variation information file of glycine max is adopted as experimental data in this *** genetic variation information of soybean is processed and the corresponding algorithm is paralleled by the OpenMP parallel *** experiment extracted the corresponding biologic information of population individuals from genetic variation information,implemented corresponding process and *** relevant serial algorithm and parallel algorithm are compared and *** experiment results show that the efficiency of the data processing and analysis of F statistic are effectively improved by OpenMP parallel technology[l].It has actual significance on processing massive bioinformatic data.

关键词： F-statistics OpenMP population differentiation variation site

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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...

引用

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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Incremental Influence Maximization for Dynamic Social Networks

Incremental Influence Maximization for Dynamic Social Networ...

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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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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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Neighbor discovery algorithm based on the regulation of duty-cycle in mobile sensor network

Neighbor discovery algorithm based on the regulation of duty...

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8th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2013

作者： Li, Jinbao Yang, Jian Zhang, Yanqing Guo, Longjiang Li, Yingshu School of Computer Science and Technology Heilongjiang University Harbin Heilongjiang 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin Heilongjiang 150080 China Department of Computer Science Georgia State University Atlanta GA 30303 United States

ISBN: (纸本)9783642397004

In this paper, aiming at the problem that the node discovers its neighbor nodes, when it is moving in mobile sensor network, we propose an algorithm for dynamical regulating the duty cycle of the node which needs to discover it neighbor node. This algorithm uses the boundary nodes in the communication range of the node to predict potential neighbor nodes, applies passion point process to predict the number of nodes in communication range of the node, regulates the duty-cycle of the node based on the model of balls and boxes, and then schedules the waking time of the node periodically by using the duty-cycle which is regulated to finish the detection. Finally, theoretical analysis and simulation experiments show that the proposed algorithm can discover more neighbor nodes in the short period of time with less energy. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Sensor nodes

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Sensitivity loss training based implicit feedback

Sensitivity loss training based implicit feedback

引用

International Conference on parallel and Distributed Systems (ICPADS)

作者： Kun Li Nan Wang Xinyu Liu Key Laboratory of Database and Parallel Computing of Heilongjiang Province School of Computer Science and Technology Heilongjiang University Harbin China

ISBN: (纸本)9781665408790

In recommender systems, due to the lack of explicit feedback features, datasets with implicit feedback are always accustomed to train all samples without separating them during model training, without considering the non-consistency of samples. This leads to a significant decrease in sample utilization and creates challenges for model training. Also, little work has been done to explore the intrinsic laws implied in the implicit feedback dataset and how to effectively train the implicit feedback data. In this paper, we first summarize the variation pattern of loss with model training for different rating samples in the explicit feedback dataset, and find that model training is highly sensitive to the ratings. Second, we design an adaptive hierarchical training function with dynamic thresholds that can effectively distinguish different rating samples in the dataset, thus optimizing the implicit feedback dataset into an explicit feedback dataset to some extent. Finally, to better learn samples with different ratings, we also propose an adaptive hierarchical training strategy to obtain better training results in the implicit feedback dataset. Extensive experiments on three datasets show that our approach achieves excellent performance and greatly improves the performance of the model.

关键词： Training Learning systems Adaptation models Sensitivity Conferences Recommender systems

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