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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11-20 订阅

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Local partition subdivision algorithm for approximate nearest neighbor query 7

Local partition subdivision algorithm for approximate neares...

引用

7th International Conference on Information Science and Control Engineering, ICISCE 2020

作者： Dong, Penghui Yang, Yan Heilongjiang University School of Computer Science and Technology Harbin China Heilongjiang Province Key Laboratory of Database and Parallel Computing Harbin China

ISBN: (纸本)9781728164069

This paper solves the problem of approximate nearest neighbor queries on high-dimensional large data sets. The two most representative methods to solve the approximate nearest neighbor query problem on high-dimensional and large-scale data sets are based on inverted multi-index and based on inverted index. The query algorithm based on the inverted multi-index requires frequent access operations to the memory, which causes more waste of resources than the query operation based on the distance order. Traditional query algorithms based on inverted indexes need to divide the entire feature space into a large number of regions to ensure the accuracy of query results when solving the problem of high-dimensional large data sets, so a large amount of space resources are required. Based on the inverted index, a query algorithm is proposed. Through the subdivision process of Voronoi Cells that are initially divided into part of the original data set, the purpose is to significantly improve the high-dimensional data set without dividing a large number of regions. On the query performance, and avoid frequent access operations to the random access memory. Theoretical analysis and experimental results show that the proposed method not only effectively improves the query processing efficiency, but also ensures the accuracy of the query. © 2020 IEEE.

关键词： Nearest neighbor search

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RETRACTED ARTICLE: Collaborative filtering based on time division

RETRACTED ARTICLE: Collaborative filtering based on time div...

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

ISBN: (纸本)9781424455386

Collaborative filtering techniques are widely used in e-commerce systems. However, the rating data are very sparse, which affects prediction accuracy greatly. A time division based collaborative filtering algorithm is proposed in this paper. According to the current time and the released time of items, items are divided into three types, named new item, normal item and old item respectively. Accordingly, users' interests are calculated in the three types respectively and user-item matrix is expanded. When predicting the rate of an item for a user, different strategies are used with different types of items. Data sparsity and new item problems are solved effectively. Empirical studies on MovieLens have shown that our newly proposed method improve recommendation quality obviously. © 2010 IEEE.

关键词： Collaborative filtering

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VDTS: A Voronoi Diagram Based Tracking Schemes in Wireless Sensor Networks 12th

VDTS: A Voronoi Diagram Based Tracking Schemes in Wireless S...

引用

12th China Wireless Sensor Network Conference, CWSN 2018

作者： Ren, Qianqian Li, Jinbao Liu, Yong Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China School of Computer Science and Technology Heilongjiang University Harbin China

ISBN: (纸本)9789811368332

Sleeping scheduling has been widely employed in target tracking due to its energy conservation. However, the randomness of target’s trajectory makes it difficult to implement with accuracy and real time guarantee. We propose VDTS, a novel, simple and efficient tracking technique. VDTS first constructs a Voronoi based network model, then makes nodes in the Voronoi polygon that the target is in work and others sleep. The target is hence detected by nodes closest to it. VDTS further presents a weighted centroid based algorithm to locate the target with the chosen nodes and reduce the influence of data noise on localization accuracy. We have implemented VDTS, and our extensive simulation show the excellent performs of our schemes. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Target tracking

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引用

11th International Conference on Information Science and Technology, ICIST 2021

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

ISBN: (纸本)9781665412667

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. © 2021 IEEE.

关键词： Graph databases

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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...

引用

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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An Incremental Partitioning Graph Similarity Search Based on Tree Structure Index 6th

An Incremental Partitioning Graph Similarity Search Based on...

引用

6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020

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

ISBN: (纸本)9789811579806

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. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Large dataset

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Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization 5

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

引用

5th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021

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

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. © 2021 IEEE.

关键词： Image fusion

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Literature recommendation based on reference graph

Literature recommendation based on reference graph

引用

International Conference on Advanced Computer Theory and Engineering

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

ISBN: (纸本)9781424465408

Research papers are frequently requested in digital library. When users query for documents about a research problem, users usually want all the related documents and the citations with the relations among them, to enable the user know the development of the research area. Traditional recommendation techniques are mainly based on similarity among users or documents to do recommendation. They do not use the relationships among documents and, especially, cannot provide topology structure of related documents to the user. This paper proposes a new recommendation technique based on reference graph of documents. Combined with traditional recommendation techniques, it can recommend research paper more completely, accurately and clearly. Experimental results show that the reference graph based recommendation technique is more effective. © 2010 IEEE.

关键词： Digital libraries

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Sensitivity loss training based implicit feedback 27

Sensitivity loss training based implicit feedback

引用

27th IEEE International Conference on parallel and Distributed Systems, ICPADS 2021

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

ISBN: (纸本)9781665408783

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. © 2021 IEEE.

关键词： adaptive hierarchical training implicit feedback sample utilization sensitive

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Negative influence maximization in social networks 4th

Negative influence maximization in social networks

引用

4th International Conference of Pioneer Computer Scientists, Engineers and Educators, ICPCSEE 2018

作者： Zhu, Jinghua Li, Bochong Zhang, Yuekai Li, Yaqiong School of Computer Science and Technology Heilongjiang University Harbin150001 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9789811322020

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 opinions. Then 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 (CELF_NIM) 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. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Economic and social effects

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