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    Keywords: Big data. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (150 pages)
    Edition: 1st ed.
    ISBN: 9789811983313
    Series Statement: Communications in Computer and Information Science Series ; v.1709
    DDC: 005.7
    Language: English
    Note: Intro -- Preface -- Organization -- Contents -- Searching Similar Trajectories Based on Shape -- 1 Introduction -- 2 Preliminaries -- 3 Align-Based Trajectory Match -- 3.1 Trajectory Preprocessing -- 3.2 Align-Based Trajectory Match -- 3.3 Distance Calculation -- 4 Symbolic Trajectory Match -- 4.1 Symbolic Representation for Trajectory -- 4.2 Symbol Distance Calculation -- 4.3 Multiple Balanced Symbol Trajectory -- 4.4 Query Processing -- 5 Experimental Study -- 5.1 Experiment Setup -- 5.2 Experiment Results -- 6 Related Work -- 6.1 Trajectory Similarity Measurement -- 6.2 Symbolic Representation -- 7 Conclusion -- References -- Unsupervised Discovery of Disentangled Interpretable Directions for Layer-Wise GAN -- 1 Introduction -- 2 Related Works -- 2.1 Generative Adversarial Networks -- 2.2 Semantic Discovery for GANs -- 2.3 Disentanglement Learning with Orthogonal Regularization -- 3 Methods -- 3.1 Overview -- 3.2 Layer-Wise Semantic Discovering Model -- 3.3 Orthogonal Jacobian Regularization -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 Non-trivial Visual Effects -- 4.3 Comparison -- 4.4 Ablation Studies -- 5 Conclusion -- References -- ASNN: Accelerated Searching for Natural Neighbors -- 1 Introduction -- 2 Related Work -- 2.1 K-Nearest Neighbor -- 2.2 Reverse k-Nearest Neighbor -- 2.3 Natural Neighbor -- 3 Proposed Method -- 3.1 Motivation and Theory -- 3.2 Accelerated Search of Natural Neighbors Algorithm -- 3.3 Complexity Analysis -- 4 Experimental Evaluation -- 4.1 Results on Synthetic Datasets -- 4.2 Results on Real-World Datasets -- 5 Conclusions -- References -- A Recommendation Algorithm for Auto Parts Based on Knowledge Graph and Convolutional Neural Network -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Knowledge Graph -- 3.2 KGCNUI Layer -- 3.3 Learning Algorithm -- 4 Experiment -- 4.1 Datasets. , 4.2 Baselines -- 4.3 Experiments Setup -- 4.4 Results -- 5 Conclusion -- References -- Identifying Urban Functional Regions by LDA Topic Model with POI Data -- 1 Introduction -- 2 Related Works -- 3 Region Functions Based on LDA Topic Model -- 3.1 Problem Statement -- 3.2 Embedded Representation of Blocks -- 3.3 Functional Region Identification -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Experimental Results and Analysis -- 5 Conclusion -- References -- A Data-to-Text Generation Model with Deduplicated Content Planning -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Word Embedding -- 3.2 Content Planning -- 3.3 Text Generation -- 3.4 Training and Inference -- 4 Experiment -- 4.1 Dataset -- 4.2 Training Configuration -- 5 Conclusion -- References -- Clustering-Enhanced Knowledge Graph Embedding -- 1 Introduction -- 2 Related Work -- 3 Problem Description -- 4 Methodology -- 4.1 KGE Models with Shared Cluster Embeddings -- 4.2 Loss Function -- 5 Experiment -- 5.1 Data Sets -- 5.2 Baseline -- 5.3 Link Prediction -- 5.4 Triplet Classification -- 6 Conclusion -- Appendix A Model parameters -- References -- FCI: Feature Cross and User Interest Network -- 1 Introduction -- 2 Related Work -- 2.1 Feature Cross Mining -- 2.2 User Behavior Sequence Mining -- 3 Our Approach -- 3.1 Problem Statement -- 3.2 Input and Output -- 3.3 Model Structure -- 3.4 Output Layer -- 3.5 Complexity Analysis -- 4 Experiment -- 4.1 Data Set -- 4.2 Evaluation Metrics -- 4.3 Model Training Details -- 4.4 Hyperparameter Settings -- 4.5 Experimental Comparison -- 4.6 Ablation Experiment -- 5 Conclusion -- References -- Author Index.
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