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

共 119 条记录，以下是71-80 订阅

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User Local and Global Interest Depth Interaction for Recommendation Algorithm

User Local and Global Interest Depth Interaction for Recomme...

引用

International Conference on Information Science and Control Engineering (ICISCE)

作者： Xufeng Zhang Yan Yang School of Computer Science Technology Heilongiiang University Harbin China Key Laboratory of Database and Parallel Computing Harbin Heilongiiang Province China

Using auxiliary information such as social networks or item attributes to improve the performance of recommender systems is a key issue in the research of recommender systems. It plays a very important role in alleviating the interactive sparsity of collaborative filtering methods. In response to this problem, a recommendation algorithm that user local and global interest depth interaction is proposed, which analyzes the user’s implicit preferences from two perspectives: based on the user’s historical behavior records, using a fully connected neural network to extract the user’s local interests; based on the user’s historical behavior items, through the association between entities in the knowledge graph, mines the entities associated with the user’s historical behavior, forming a multi-layer global interest layer to generalize user interests. The user’s local interest vector activates the item entity in the global interest layer to generate the user’s global interest vector. Finally, the deep neural network is used to complete the feature interaction of users’ local interests, global interests and recommended items. The user’s local and global interests accurately describe user preferences and improve the accuracy of click-through rate prediction. Experiments show that the recommendation performance of the algorithm on the two public data sets is better than the comparison baseline and the classic recommendation algorithm.

关键词： Knowledge engineering Deep learning Information science Control engineering Social networking (online) Neural networks Feature extraction

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A probabilistic group reverse k-nearest-neighbor query in sensor networks 1

引用

7th China Conference of Wireless Sensor Networks, CWSN 2013

作者： Zhu, Jinghua Kan, Bin Liu, Yong Wang, Tong Pan, Liqiang Liu, Dan School of Computer Science and Technology Heilongjiang University Harbin 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin 150080 China College of Information and Communication Engineering Harbin Engineering University Harbin 150001 China School of Computer and Science Technology Harbin School of Technology Harbin 150001 China School of Computer Science Northeast Forestry University Harbin 150001 China

ISBN: (数字)9783642541742

ISBN: (纸本)9783642541735

Group Reverse k-Nearest-Neighbor Query (GRkNN) can be used to evaluate the influences of query objects and has wide applications. Traditional algorithms are not able to obtain satisfied results for uncertain sensor network data. A probabilistic threshold group reverse k nearest neighbor query (PT-GRkNN) is proposed in this paper. PT-GRkNN exploits filter-refine framework, geometric filter and probability filter are proposed to shrink the search space, the final query results can be obtained by refine phase. Experimental results show that the efficiency of PT-GRkNN is better than the existing methods. © 2014 Springer-Verlag Berlin Heidelberg.

关键词： Sensor networks

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International Conference on Information Science and Technology (ICIST)

作者： Zhongqing Wang Yan Yang Yingli Zhong School of Computer Science Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

Graph similarity search is an important research problem in many applications, such as finding result graphs that have a similar structure to a given entity in biochemistry, data mining, and pattern recognition. Top-k graph similarity search is one of graph similarity search tasks, which aims to find the top-k graphs that are most similar to the query graph in a given graph database. In this paper, the top-k similarity search problem based on the graph edit distance is studied according to the corollary of the partitioned similarity theorem. Firstly, in order to speed up the online search process and avoid scanning each graph in the database one by one, an offline hierarchical inverted index is constructed to satisfy top-k search. Secondly, the offline hierarchical inverted index is used to filter the candidate graphs online and verify them, which reduces the time of searching the graphs. Finally, the good performance of the algorithm in running time and scalability is verified by running the similarity algorithm on real dataset and synthetic dataset.

关键词： Information science databases Scalability Filtering algorithms Search problems Partitioning algorithms Indexes

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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 ...

引用

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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Notice of Retraction: Collaborative filtering based on time division

Notice of Retraction: Collaborative filtering based on time ...

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International Conference on Computer Science and Information Technology (CSIT)

作者： Yan Yang Long Yun Key Laboratory of Database and Parallel Computing of Heilongjiang Province Department of Computer Science and Technology Heilongjiang University Harbin China

This article has been retracted by the publisher.

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Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization

Visible-Infrared Image Fusion Based on Double- Density Wavel...

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

作者： Hao Guo Jingyu Chen Xuan Yang Qingliang Jiao Ming Liu Beijing Institute of Environmental Features Beijing China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

Infrared and visible image fusion has been a hot issue in image fusion. However, the parameters and result image have many proposed. In this paper, a novel visible infrared image fusion algorithm based on double-density wavelet and thermal exchange optimization is proposed. The pre-processed infrared and visible images are decomposed into detail layers and background layers by double-density wavelet transform. Thermal exchange optimization is used to estimate the number of layers and weight thresholds of decomposition. Experimental shows that both visual effects and quantitative analysis of proposed algorithm can get the best results.

关键词： Wavelet transforms Thermal decomposition Wavelet analysis Visual effects Thermal analysis Image fusion Optimization

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A New Feature Fusion Method Based on Pre-Training Model for Sequence Labeling

A New Feature Fusion Method Based on Pre-Training Model for ...

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International Conference on Data Storage and Data Engineering (DSDE)

作者： Shichuan Yu Yan Yang School of computer science and technology Heilongjiang University Harbin China Heilongjiang Key Laboratory of Database and Parallel Computing Heilongjiang University Harbin China

To fuse vocabulary features into the pre-training model is the mainstream data feature processing method for sequence labelling tasks. In general, the feature fusion methods that have been proposed at present are direct fusion outside the pre-training model or fusion of lexical features using attention mechanism. However, the study found that this way of vocabulary enhancement does not conform to the word formation rules of modern Chinese. In the Chinese language, it is easy to fuse irrelevant or even incorrect lexical features into the sequence using the above feature processing methods, which is bad for the experimental results of the Chinese sequence labelling task. To solve these problems, we propose to use Cosine Similarity Adapter to process lexical features in Chinese sequence labelling tasks. CSBERT is a hybrid model using this structure based on BERT, which conforms to the word formation rules of modern Chinese to a certain extent. It can fuse the features of the word into the character or eliminate the features of the word in the character according to the cosine similarity between the character vector and a word vector. The experimental results show that CSBERT has better ability to label Chinese sequences than the benchmark model. CSBERT has achieved the best experimental results such as F1-Score on 7 open datasets and the best ability of multi-label classification, which proves that the model has good practical value.

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Implementing the jacobi algorithm for solving eigenvalues of symmetric matrices with CUDA

Implementing the jacobi algorithm for solving eigenvalues of...

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2012 IEEE 7th International Conference on Networking, Architecture and Storage, NAS 2012

作者： Wang, Tao Guo, Longjiang Li, Guilin Li, Jinbao Wang, Renda Ren, Meirui He, Jing School of Computer Science and Technology Heilongjiang University Harbin 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin 150080 China Software School of Xiamen University Xiamen Fujian 361005 China Department of Computer Science Kennesaw State University Kennesaw GA 30144 United States

ISBN: (纸本)9780769547220

Solving the eigenvalues of matrices is an open problem which is often related to scientific computation. With the increasing of the order of matrices, traditional sequential algorithms are unable to meet the needs for the calculation time. Although people can use cluster systems in a short time to solve the eigenvalues of large-scale matrices, it will bring an increase in equipment costs and power consumption. This paper proposes a parallel algorithm named Jacobi on gpu which is implemented by CUDA (Computer Unified Device Architecture) on GPU (Graphic Process Unit) to solve the eigenvalues of symmetric matrices. In our experimental environment, we have Intel Core i5-760 quad-core CPU, NVIDIA GeForce GTX460 card, and Win7 64-bit operating system. When the size of matrix is 10240×10240, the number of iterations is 10000 times, the speedup ratio is 13.71. As the size of matrices increase, the speedup ratio increases correspondingly. Moreover, as the number of iterations increases, the speedup ratio is very stable. When the size of matrix is 8192×8192, the number of iterations are 1000, 2000, 4000, 8000 and 16000 respectively, the standard deviation of the speedup ratio is 0.1161. The experimental results show that the Jacobi on gpu algorithm can save more running time than traditional sequential algorithms and the speedup ratio is 3.02∼13.71. Therefore, the computing.time of traditional sequential algorithms to solve the eigenvalues of matrices is reduced significantly. © 2012 IEEE.

关键词： Iterative methods

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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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OCO: A Multi-channel MAC Protocol with Opportunistic Cooperation for Wireless Sensor Networks

OCO: A Multi-channel MAC Protocol with Opportunistic Coopera...

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IEEE/IFIP International Conference on Embedded and Ubiquitous computing. EUC

作者： Jinbao Li Desheng Zhang Longjiang Guo School of Computer Science and Technology Heilongjiang University Harbin Heilongjiang China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin Heilongjiang China

To handle the triple hidden terminal problems, this paper proposes OCO, an asynchronous multi-channel MAC protocol with opportunistic cooperation for wireless sensor networks. By adopting opportunistic cooperation, OCO effectively alleviates, if not eliminates, the triple hidden terminal problems. More importantly, OCO is fully distributed with no requirements of time synchronization or multi-radio scheme, so it is easy to be implemented on the real sensor nodes. Via the theoretical analysis, the opportunistic probability that a node cooperates with its neighbor is obtained. To validate the effectiveness of opportunistic cooperation, extensive simulations and real test bed experiments were con-ducted. The simulation and experimental results show that when the number of channels is large or the network loads are heavy, OCO improves energy efficiency and throughput significantly compared with other works in the literature.

关键词： Receivers Wireless sensor networks Throughput Ad hoc networks Media Access Protocol Media

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