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< Page ,Total 264 >
Improving Object Retrieval Quality by Integration of Similarity Propagation and Query Expansion EI Scopus SCIE
期刊论文 | 2019 , 21 (3) , 760-770 | IEEE Transactions on Multimedia
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Abstract :

Re-ranking is an essential step for accurate image retrieval, due to its well known power in performance improvement. Although numerous works have been proposed for re-ranking, many of them are only customized for a certain image representation model. In contrast to most existing techniques, we develop generalized re-ranking algorithms that are applicable to different kinds of image encodings in this paper. We first employ a quite successful theory of similarity propagation to reconstruct vectors of a query and its top ranked images, and subsequently get a re-ranked list by comparing the new image vectors. Furthermore, considering that the just mentioned strategy is directly compatible with query expansion, and thus in order to leverage advantages of this milestone, we then propose to integrate them into a unified framework for maximizing re-ranking benefits. Our re-ranking algorithms are memory and computation efficient, and experimental results on benchmark datasets demonstrate that they compare favorably with the state-of-the-art. Our code is available at https://github.com/MaJinWakeUp/rerank. IEEE

Keyword :

Benchmark datasets Image representations Object retrieval Performance improvements Query expansion Re-ranking Similarity propagation Unified framework

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GB/T 7714 Pang, Shanmin , Ma, Jin , Zhu, Jihua et al. Improving Object Retrieval Quality by Integration of Similarity Propagation and Query Expansion [J]. | IEEE Transactions on Multimedia , 2019 , 21 (3) : 760-770 .
MLA Pang, Shanmin et al. "Improving Object Retrieval Quality by Integration of Similarity Propagation and Query Expansion" . | IEEE Transactions on Multimedia 21 . 3 (2019) : 760-770 .
APA Pang, Shanmin , Ma, Jin , Zhu, Jihua , Xue, Jianru , Tian, Qi . Improving Object Retrieval Quality by Integration of Similarity Propagation and Query Expansion . | IEEE Transactions on Multimedia , 2019 , 21 (3) , 760-770 .
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Joint Model Feature Regression and Topic Learning for Global Citation Recommendation SCIE
期刊论文 | 2019 , 7 , 1706-1720 | IEEE ACCESS
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Abstract :

Citation recommendation has gained increasing attention in recent years. In practice, researchers usually prefer to cite the most topic-relevant articles. Nevertheless, how to model the implicit correlations between topics and citations is still a challenging task. In this paper, we propose a novel citation recommendation model, called TopicCite, which mines such fine-grained correlations. We extract various citation features from citation network, and integrate the learning process of feature regression with topic modeling. At the recommendation stage, we expand the folding-in process by adding the topic influence of papers that correlated with user-provided information. TopicCite can also be considered a technique for extracting topic-related citation features from manually defined citation features, which can essentially improve the granularity of pre-extracted features. In addition, the unsupervised topic model is supervised and mutually reinforced by abundant citation features in TopicCite; thus, the proposed model can also extract more reliable topic distributions from citation data, which brings a new perspective to topic discovery on linked data. The experimental results on the AAN and DBLP datasets demonstrate that our model is competitive with the state-of-the-art methods.

Keyword :

Citation recommendation feature regression topic model

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GB/T 7714 Dai, Tao , Zhu, Li , Wang, Yifan et al. Joint Model Feature Regression and Topic Learning for Global Citation Recommendation [J]. | IEEE ACCESS , 2019 , 7 : 1706-1720 .
MLA Dai, Tao et al. "Joint Model Feature Regression and Topic Learning for Global Citation Recommendation" . | IEEE ACCESS 7 (2019) : 1706-1720 .
APA Dai, Tao , Zhu, Li , Wang, Yifan , Zhang, Hongfei , Cai, Xiaoyan , Zheng, Yu . Joint Model Feature Regression and Topic Learning for Global Citation Recommendation . | IEEE ACCESS , 2019 , 7 , 1706-1720 .
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Multi-view spectral clustering via partial sum minimisation of singular values SCIE
期刊论文 | 2019 , 55 (6) , 314-315 | ELECTRONICS LETTERS
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Abstract :

This Letter proposes a robust multi-view spectral clustering approach. It first calculates a normalised graph Laplacian for each single view, and then uses them to recover a shared low-rank Laplacian by the low rank and sparse matrix decomposition. To achieve matrix decomposition, partial sum minimisation of singular values is leveraged to design a novel objective function, which can be optimised by the augmented Lagrangian multiplier algorithm to recover a common normalised graph Laplacian. Accordingly, multi-view clustering results can be obtained by taking spectral clustering on the common Laplacian. Experimental results illustrate its effectiveness over other related approaches.

Keyword :

singular values pattern clustering graph theory single view common normalised graph Laplacian low rank sparse matrices augmented Lagrangian multiplier algorithm common Laplacian robust multiview spectral clustering approach partial sum minimisation low-rank Laplacian multiview clustering results matrix decomposition optimisation

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GB/T 7714 Zhai, Ling , Zhu, Jihua , Zheng, Qinghai et al. Multi-view spectral clustering via partial sum minimisation of singular values [J]. | ELECTRONICS LETTERS , 2019 , 55 (6) : 314-315 .
MLA Zhai, Ling et al. "Multi-view spectral clustering via partial sum minimisation of singular values" . | ELECTRONICS LETTERS 55 . 6 (2019) : 314-315 .
APA Zhai, Ling , Zhu, Jihua , Zheng, Qinghai , Pang, Shanmin , Li, Zhongyu , Wang, Jun . Multi-view spectral clustering via partial sum minimisation of singular values . | ELECTRONICS LETTERS , 2019 , 55 (6) , 314-315 .
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Bibliographic Network Representation Based Personalized Citation Recommendation SCIE
期刊论文 | 2019 , 7 , 457-467 | IEEE ACCESS
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Abstract :

With the increasing number of scientific papers, researchers find it more and more difficult to obtain relevant and appropriate papers to cite. Citation recommendation aims to overcome this problem by providing a reference paper list for a given manuscript. In this paper, we propose a bibliographic network representation (BNR) model, which simultaneously incorporates bibliographic network structure and content of different kinds of objects (authors, papers, and venues) for efficient recommendation. The proposed model also makes personalized citation recommendation possible, which is a new issue that a few papers addressed in the past. When conducting experiments on the ACL Anthology Network and DBLP datasets, the results demonstrate that the proposed BNR-based citation recommendation approach is able to achieve considerable improvement over other network representation-based citation recommendation approaches. The performance of the personalized recommendation approach is also competitive with the non-personalized recommendation approach.

Keyword :

personalized citation recommendation network representation Bibliographic network

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GB/T 7714 Cai, Xiaoyan , Zheng, Yu , Yang, Libin et al. Bibliographic Network Representation Based Personalized Citation Recommendation [J]. | IEEE ACCESS , 2019 , 7 : 457-467 .
MLA Cai, Xiaoyan et al. "Bibliographic Network Representation Based Personalized Citation Recommendation" . | IEEE ACCESS 7 (2019) : 457-467 .
APA Cai, Xiaoyan , Zheng, Yu , Yang, Libin , Dai, Tao , Guo, Lantian . Bibliographic Network Representation Based Personalized Citation Recommendation . | IEEE ACCESS , 2019 , 7 , 457-467 .
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Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision Scopus SSCI SCIE
期刊论文 | 2019 , 83 , 1-13 | Omega (United Kingdom)
WoS CC Cited Count: 3 SCOPUS Cited Count: 5
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Abstract :

© 2018 Elsevier Ltd. We propose a new multiple criteria decision aiding approach for market segmentation that integrates preference analysis and segmentation decision within a unified framework. The approach employs an additive value function as the preference model and requires consumers to provide pairwise comparisons of some products as the preference information. To analyze each consumer's preferences, the approach applies the disaggregation paradigm and the stochastic multicriteria acceptability analysis to derive a set of value functions according to the preference information provided by each consumer. Then, each consumer's preferences can be represented by the distribution of possible rankings of products and associated support degrees by applying the derived value functions. On the basis of preference analysis, a new metric is proposed to measure the similarity between preferences of different consumers, and a hierarchical clustering algorithm is developed to perform market segmentation. To help firms serve consumers from different segments with targeted marketing policies and appropriate products, the approach proposes to work out a representative value function and the univocal ranking of products for each consumer so that products that rank in the front of the list can be presented to her/him. Finally, an illustrative example of a market segmentation problem details the application of the proposed approach.

Keyword :

Clustering analysis Market segmentation Multiple criteria decision aiding Preference modeling

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GB/T 7714 Liu, Jiapeng , Liao, Xiuwu , Huang, Wei et al. Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision [J]. | Omega (United Kingdom) , 2019 , 83 : 1-13 .
MLA Liu, Jiapeng et al. "Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision" . | Omega (United Kingdom) 83 (2019) : 1-13 .
APA Liu, Jiapeng , Liao, Xiuwu , Huang, Wei , Liao, Xianzhao . Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision . | Omega (United Kingdom) , 2019 , 83 , 1-13 .
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A two-level finite element method for the Allen–Cahn equation EI Scopus SCIE
期刊论文 | 2019 , 96 (1) , 158-169 | International Journal of Computer Mathematics
WoS CC Cited Count: 1 SCOPUS Cited Count: 1
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Abstract :

We consider the fully implicit treatment for the nonlinear term of the Allen–Cahn equation. To solve the nonlinear problem efficiently, the two-level scheme is employed. We obtain the discrete energy law of the fully implicit scheme and two-level scheme with finite element method. Also, the convergence of the two-level method is presented. Finally, some numerical experiments are provided to confirm the theoretical analysis. © 2018 Informa UK Limited, trading as Taylor & Francis Group

Keyword :

Discrete energies Fully implicit scheme Implicit treatment Nonlinear problems Numerical experiments Numerical tests Stability and convergence Two level methods

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GB/T 7714 Liu, Qingfang , Zhang, Ke , Wang, Zhiheng et al. A two-level finite element method for the Allen–Cahn equation [J]. | International Journal of Computer Mathematics , 2019 , 96 (1) : 158-169 .
MLA Liu, Qingfang et al. "A two-level finite element method for the Allen–Cahn equation" . | International Journal of Computer Mathematics 96 . 1 (2019) : 158-169 .
APA Liu, Qingfang , Zhang, Ke , Wang, Zhiheng , Zhao, Jiakun . A two-level finite element method for the Allen–Cahn equation . | International Journal of Computer Mathematics , 2019 , 96 (1) , 158-169 .
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Robust point cloud registration based on both hard and soft assignments EI Scopus SCIE
期刊论文 | 2019 , 110 , 202-208 | Optics and Laser Technology
WoS CC Cited Count: 1
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For the registration of partially overlapping point clouds, this paper proposes an effective approach based on both the hard and soft assignments. Given two initially posed clouds, it firstly establishes the forward correspondence for each point in the data shape and calculates the value of a binary variable, which indicates whether this point correspondence is located in the overlapping areas or not. Then, it establishes the bilateral correspondence and computes bidirectional distances for each point in the overlapping areas. Based on the ratio of bidirectional distances, the exponential function is selected and utilized to calculate the probability value, which indicates the reliability of the point correspondence. Subsequently, both the values of hard and soft assignments are embedded into the proposed objective function for registration of partially overlapping point clouds, which then be solved by the proposed variant of ICP algorithm to obtain the optimal rigid transformation. The proposed approach can achieve good registration of point clouds, even when their overlap percentage is low. Experimental results tested on public datasets illustrate its superiority over previous approaches on accuracy and robustness. © 2018 Elsevier Ltd

Keyword :

Bidirectional distances Hard assignment Overlap percentage Point cloud registration Soft assignments

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GB/T 7714 Zhu, Jihua , Jin, Congcong , Jiang, Zutao et al. Robust point cloud registration based on both hard and soft assignments [J]. | Optics and Laser Technology , 2019 , 110 : 202-208 .
MLA Zhu, Jihua et al. "Robust point cloud registration based on both hard and soft assignments" . | Optics and Laser Technology 110 (2019) : 202-208 .
APA Zhu, Jihua , Jin, Congcong , Jiang, Zutao , Xu, Siyu , Xu, Minmin , Pang, Shanmin . Robust point cloud registration based on both hard and soft assignments . | Optics and Laser Technology , 2019 , 110 , 202-208 .
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A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving EI Scopus SCIE
期刊论文 | 2019 , 100 (5-8) , 1635-1645 | International Journal of Advanced Manufacturing Technology
WoS CC Cited Count: 2 SCOPUS Cited Count: 1
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Abstract :

As a particular two degree of freedom generating method, skiving is effective to manufacture the periodically distributed internal and external profiles, and its cutting edge design is a foundational problem. In order to avoid the singularity in analytical methods, this paper studied a discrete surface assisted universal method to identify the cutting edge of skiving cutter and simulate the machining process by discrete cutting points. Firstly, the kinematic model of skiving was constructed in aspects of the parametrical modeling of the cutter and workpiece as well as the machining configuration. The principle of cutting edge identification was investigated based on the conjugation process of skiving in the following. Then, the entire procedure for cutting edge calculation was presented in detail. Therefrom, according to the profile generation during cutting action, the skiving spatial contacts were analyzed through reasonable coordinate frame transformation. At last, an external skiving for involute gear was taken, the cutting edges for two kinds of rake flank were calculated, and the machining error between the machined profile and desired profile was compared to proof the correctness of calculated cutting edges. Besides, the analysis of the spatial contact motions for these cases validated the effectiveness and the practicality of the proposed method. © 2018, Springer-Verlag London Ltd., part of Springer Nature.

Keyword :

Contact curves Cutting edges Kinematic model Machining process simulation Skiving

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GB/T 7714 Jia, Kang , Zheng, Shuai , Guo, Junkang et al. A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving [J]. | International Journal of Advanced Manufacturing Technology , 2019 , 100 (5-8) : 1635-1645 .
MLA Jia, Kang et al. "A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving" . | International Journal of Advanced Manufacturing Technology 100 . 5-8 (2019) : 1635-1645 .
APA Jia, Kang , Zheng, Shuai , Guo, Junkang , Hong, Jun . A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving . | International Journal of Advanced Manufacturing Technology , 2019 , 100 (5-8) , 1635-1645 .
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Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation EI Scopus SCIE
期刊论文 | 2019 , 28 (2) , 841-852 | IEEE Transactions on Image Processing
WoS CC Cited Count: 1 SCOPUS Cited Count: 1
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Abstract :

© 1992-2012 IEEE. Embedding and aggregating a set of local descriptors (e.g., SIFT) into a single vector is normally used to represent images in image search. Standard aggregation operations include sum and weighted aggregations. While showing high efficiency, sum aggregation lacks discriminative power. In contrast, weighted aggregation shows promising retrieval performance but suffers extremely high time cost. In this paper, we present a general mixed aggregation method that unifies sum and weighted aggregation methods. Owing to its general formulation, our method is able to balance the trade-off between retrieval quality and image representation efficiency. Additionally, to improve query performance, we propose computing multiple weighting coefficients rather than one for each to be aggregated vector by partitioning them into several components with negligible computational cost. Extensive experimental results on standard public image retrieval benchmarks demonstrate that our aggregation method achieves state-of-the-art performance while showing over ten times speedup over baselines.

Keyword :

Aggregation image representation image search multiple weights

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GB/T 7714 Pang, Shanmin , Xue, Jianru , Zhu, Jihua et al. Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation [J]. | IEEE Transactions on Image Processing , 2019 , 28 (2) : 841-852 .
MLA Pang, Shanmin et al. "Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation" . | IEEE Transactions on Image Processing 28 . 2 (2019) : 841-852 .
APA Pang, Shanmin , Xue, Jianru , Zhu, Jihua , Zhu, Li , Tian, Qi . Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation . | IEEE Transactions on Image Processing , 2019 , 28 (2) , 841-852 .
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FPFH-Based Graph Matching for 3D Point Cloud Registration EI CPCI-S Scopus
会议论文 | 2018 , 10696 | 10th International Conference on Machine Vision (ICMV)
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Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n(3))-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.

Keyword :

Point cloud registration initial alignment set partitioning correspondences graph matching

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GB/T 7714 Zhao, Jiapeng , Li, Chen , Tian, Lihua et al. FPFH-Based Graph Matching for 3D Point Cloud Registration [C] . 2018 .
MLA Zhao, Jiapeng et al. "FPFH-Based Graph Matching for 3D Point Cloud Registration" . (2018) .
APA Zhao, Jiapeng , Li, Chen , Tian, Lihua , Zhu, Jihua . FPFH-Based Graph Matching for 3D Point Cloud Registration . (2018) .
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