Database Systems for Advanced Applications

Name: Database Systems for Advanced Applications | 23rd International Conference, DASFAA 2018, Gold Coast, QLD, Australia, May 21-24, 2018, Proceedings, Part I
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23rd International Conference, DASFAA 2018, Gold Coast, QLD, Australia, May 21-24, 2018, Proceedings, Part I

Jian Pei Yannis Manolopoulos Shazia Sadiq Jianxin Li(Editor)

Springer (Publisher)

Published on 16. May 2018

XXIV, 938 pages

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978-3-319-91452-7 (ISBN)

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Content

Intro
Preface
Organization
Contents -- Part I
Contents -- Part II
Network Embedding
Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective
1 Introduction
2 Related Work
2.1 Network Embedding
2.2 Matrix Factorization and Word Embedding
3 Network Embedding with Matrix Factorization
3.1 High-Order Proximity Preserving Matrix
3.2 Incorporating Label Context
3.3 Joint Matrix Factorization
3.4 Optimization
4 Experiments
4.1 Semi-supervised Node Classification
4.2 Link Prediction
4.3 Case Study
5 Conclusion
References
Attributed Network Embedding with Micro-meso Structure
1 Introduction
2 Related Work
3 The Proposed Model
3.1 Modeling the Microscopic Proximity Structure
3.2 Modeling the Mesoscopic Community Structure
3.3 Modeling the Node Attributes
3.4 The Overall Objective Function
4 Optimization
4.1 Complexity Analysis
5 Experiments
5.1 Experimental Settings
5.2 Parameter Analysis
5.3 Convergence Analysis
5.4 Comparison Results with the Existing Algorithms
5.5 Comparison Results with Its Variations
6 Conclusions
References
An Efficient Exact Nearest Neighbor Search by Compounded Embedding
1 Introduction
2 Preliminaries
3 Embedding and Distance Lower Bound
3.1 Motivation
3.2 Embedding Method
3.3 Correctness of Our Distance Lower Bound
3.4 Optimization of Our Distance Lower Bound
3.5 Using PCA Technique
4 Our Exact NNS Algorithm
4.1 Motivation
4.2 Exact NNS Algorithm
4.3 Performance Analysis
5 Experiment
5.1 Experimental Setting
5.2 Exact Nearest Neighbor Search
6 Conclusion
References
BASSI: Balance and Status Combined Signed Network Embedding
1 Introduction
2 The Proposed BASSI Model
2.1 Balance Theory and Status Theory
2.2 Modeling Balance Theory
2.3 Modeling Status Theory
2.4 BASSI Model
3 Experimental Evaluation on Sign Prediction
3.1 Settings
3.2 Results for Sign Prediction
4 Experimental Evaluation on Node Ranking
5 Conclusion
References
Recommendation
Geographical Relevance Model for Long Tail Point-of-Interest Recommendation
1 Introduction
2 Preliminaries
2.1 Related Work
2.2 Problem Definition
3 Geographical Relevance Model
4 Performance Evaluation
4.1 Experimental Settings
4.2 Experimental Results
5 Conclusions
References
Exploiting Context Graph Attention for POI Recommendation in Location-Based Social Networks
1 Introduction
2 Problem Description
3 The Context Graph Attention Model
3.1 Context Graphs in LBSN
3.2 Attentive Representations for Users and POIs in Context Graphs
3.3 Solution Framework
4 Attention Computation and Model Learning
4.1 Context-Aware Attention for Friends and Neighbors
4.2 Dual Attention for User-POI Context Graph
4.3 POI Visiting Probability Prediction
4.4 Model Training
5 Experiments
5.1 Settings
5.2 Overall Performance
5.3 Effectiveness of Different Attention Networks
5.4 Parameter Sensitivity Test
6 Related Works
6.1 POI Recommendation
6.2 Attention Mechanism
7 Conclusions
References
Restricted Boltzmann Machine Based Active Learning for Sparse Recommendation
1 Introduction
2 Related Work
3 Problem Formulation
4 Proposed Approach
4.1 Overview
4.2 User Preference Learning
4.3 Adaptive Item Selection
4.4 Making Recommendation
5 Experiments
5.1 Experimental Setup
5.2 Recommendation Effectiveness
5.3 Further Discussions
6 Conclusion
References
Discrete Binary Hashing Towards Efficient Fashion Recommendation
1 Introduction
2 Related Work
2.1 Fashion Recommendation
2.2 Hashing
3 Methodology
3.1 Problem Formulation
3.2 Kernelized Feature Embedding
3.3 Optimization
4 Experimental Dataset
4.1 Fashion Dataset
4.2 Feature Extraction
4.3 Description of Matching Matrix
4.4 Data Preprocessing
4.5 Matching Matrix Self-augmentation
5 Experiment
5.1 Evaluation Metrics
5.2 Compared Approaches
5.3 Implementation Settings
5.4 Experiment Results
5.5 Self-augmentation Study
5.6 Discrete or Not?
5.7 Parameter Sensitivity Experiment
6 Conclusion
References
Learning Dual Preferences with Non-negative Matrix Tri-Factorization for Top-N Recommender System
1 Introduction
2 Related Work
2.1 Matrix Factorization
2.2 Topic-Based Recommendations
3 User-Product Topic Model
3.1 Problem Definition
3.2 Generative Process
3.3 Parameter Estimation
4 Experiments
4.1 Datasets
4.2 Comparisons and Evaluation
4.3 Experimental Setting
4.4 Performance Comparison
4.5 Influence of the Number of Topics
4.6 Impact of Training Data Size
4.7 Parameter Effect Analysis
5 Conclusions
References
Low-Rank and Sparse Cross-Domain Recommendation Algorithm
1 Introduction
2 The Proposed Algorithm
3 Experiments
3.1 Datasets and Evaluation Measures
3.2 Comparison Experiments
4 Conclusion
References
Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mapping
1 Introduction
2 Related Work
3 Matrix Factorization by Incorporating User Similarities
3.1 Rating Behavior Based User Similarity Measures
3.2 Rating Matrix Factorization
4 Neighborhood Based Latent Feature Mapping
5 Experiments
5.1 Experiment Setup
5.2 Experimental Results
6 Conclusions
References
Graph and Network Data Processing
K-Connected Cores Computation in Large Dual Networks
1 Introduction
2 Preliminaries
3 Computing K-Connected Cores
4 Computing Maximal-Connected Cores
4.1 A Bottom-Up Approach
4.2 A Top-Down Approach
4.3 Binary Searching MCCOs
5 Experiments
5.1 Performance Studies on Real-World Datasets
5.2 Scalability Testing
5.3 Performance Studies on Synthetic Datasets
5.4 Effectiveness Evaluation
6 Related Works
7 Conclusion
References
Graph Clustering with Local Density-Cut
1 Introduction
2 Related Work
3 Graph Clustering Based on Density-Cut
3.1 Local Density Measure
3.2 Density-Connected Tree
3.3 The Dcut Algorithm
4 Experiments
4.1 Synthetic Data
4.2 Real World Data
4.3 Case Study
4.4 Runtime
5 Conclusions
References
External Topological Sorting in Large Graphs
1 Introduction
2 Preliminaries
3 Existing Solutions
3.1 Semi-external Topological Sorting Algorithm
3.2 External Memory Topological Sorting Algorithm
3.3 Drawbacks of Existing Solutions
4 A New Approach
4.1 Contraction-Expansion Paradigm
4.2 Contraction Phase
4.3 Expansion Phase
4.4 Our Approach
5 Performance Studies
6 Related Work
7 Conclusion
References
Finding All Nearest Neighbors with a Single Graph Traversal
1 Introduction
2 Preliminaries
3 VIVET
3.1 Precomputation
3.2 Query Processing
3.3 Generalizing the Algorithm
3.4 Algorithm Complexity
4 Experiments
4.1 Experimental Setup
4.2 Precomputation Costs
4.3 Query Costs
4.4 Experiments on Directed Graphs
5 Related Work
6 Conclusion
References
Towards Efficient Path Skyline Computation in Bicriteria Networks
1 Introduction
2 Related Work
3 Preliminaries
4 Existing Solution
5 Our New Approach
6 Performance Studies
7 Conclusion
References
Answering Why-Not Questions on Structural Graph Clustering
1 Introduction
2 Related Work and Problem Statement
2.1 Related Work
2.2 Preliminary
2.3 Problem Definition
3 Influence Factors for pSCAN
3.1 An Explanation Framework
3.2 The Analysis of
3.3 The Analysis of
4 Explanation Algorithms
4.1 Modifying the Similarity Threshold
4.2 Modifying the Density Constraint
5 Experiments
5.1 Experimental Setup
5.2 Performance Evaluation
6 Conclusion
References
SSRW: A Scalable Algorithm for Estimating Graphlet Statistics Based on Random Walk
1 Introduction
2 Preliminaries
2.1 Notations and Definitions
2.2 Random Walk
3 The Scalable Subgraph Sampling Algorithm
3.1 Sampling Strategy for k-Subgraphs
3.2 Computation of Repeat Coefficient
3.3 Unbiased Estimator
3.4 Framework to Estimate Graphlet Counts and Bound Analysis
4 Experiments
4.1 Experiment Setup
4.2 Estimation of 6-and 7-Graphlet Statistics
4.3 Parallelization
4.4 Comparison with Previous Work
4.5 Runtime Comparison
5 Related Work
6 Conclusion
References
Multi-metric Graph Query Performance Prediction
1 Introduction
2 Problem Formulation
2.1 Graph Queries
2.2 Performance Metrics
2.3 Performance Prediction
3 The Framework
3.1 Learning Phase
3.2 Prediction Phase
4 Workload Optimization
5 Experimental Evaluation
6 Conclusion
References
A Privacy-Preserving Framework for Subgraph Pattern Matching in Cloud
1 Introduction
2 Related Work
3 Problem Formulation
4 Privacy Preserving in Cloud
4.1 Structural Privacy
4.2 Label Privacy
4.3 Outsourced Graph
4.4 Result Processing
5 Experimental Study
5.1 Datasets and Setup
5.2 Experiments Analysis
6 Conclusion
References
Adaptive and Parallel Data Acquisition from Online Big Graphs
Abstract
1 Introduction
2 Adaptive Data Collection Based on QMC Sampling
2.1 Basic Idea and Algorithm
2.2 Analysis
3 Experimental Results
3.1 Experiment Setup
3.2 Effectiveness
3.3 Efficiency
4 Conclusion
Acknowledgment
References
Answering the Why-Not Questions of Graph Query Autocompletion
1 Introduction
2 Searching for the Answers to the Why-Not Questions
2.1 Illustrations of the Search for * (search_*) and * (search_*)
2.2 Search for the Proper Suggestion Ranking Preference (search_*)
3 Experimental Evaluation
4 Conclusion
References
Exploiting Reshaping Subgraphs from Bilateral Propagation Graphs
1 Introduction
2 Problem Statement
2.1 Preliminary Concepts
3 Methodology
3.1 Multi-aspect Temporal Property
3.2 Sequential Time Property
4 Experiment
4.1 Evaluation Metric
4.2 Estimating Reshaping Subgraphs via Trigger
5 Related Work
6 Conclusion
References
Social Network Analytics
Sample Location Selection for Efficient Distance-Aware Influence Maximization in Geo-Social Networks
1 Introduction
2 Related Work
3 Preliminary and Problem Definition
3.1 Distance-Aware Influence Maximization
3.2 Problem Definition
4 Sample Location Selection
4.1 Methodology
4.2 Algorithm
5 Experiments
5.1 Setup
5.2 Effectiveness Analysis
5.3 Efficiency Analysis
5.4 Anchor Point Selection Strategy Analysis
6 Conclusion
References
Identifying Topical Opinion Leaders in Social Community Question Answering
1 Introduction
2 Related Work
3 Dataset
3.1 Dataset Collection
3.2 Initial Analysis
4 Topical Opinion Leader Identification in SCQA
4.1 Topic-Sensitive Influence Measure
4.2 Topic-Relevant Expertise Measure
5 Experiments and Evaluation
5.1 Baseline Algorithms and Evaluation Metrics
5.2 Performance Evaluation
5.3 User Study
6 Conclusion
References
Personalized Geo-Social Group Queries in Location-Based Social Networks
1 Introduction
2 Problem Formulation
3 PGSG Query Processing
3.1 Baseline Algorithm
3.2 Group-Venue Pattern Search
4 TkPGSG Query Processing
5 Experiments
5.1 Experimental Settings
5.2 Experimental Results
6 Related Works
7 Conclusions
References
Tracking Dynamic Magnet Communities: Insights from a Network Perspective
1 Introduction
2 Preliminaries
2.1 Community Projected Flow Network Construction
2.2 Dynamic Magnet Community Detection
3 Dynamic Magnet Community Model
3.1 Community Projected Flow Network Construction
3.2 Measuring Dynamic Magnet Score
4 Experiments
4.1 Experimental Settings
4.2 Evaluation for Detection Results
4.3 Model Analysis
4.4 Dynamic Magnet Score Application Case Study
5 Related Work
5.1 Influence Analysis
5.2 Time Series Modeling
5.3 Community Characterization
6 Conclusion
References
Discovering Strong Communities with User Engagement and Tie Strength
1 Introduction
2 Problem Definition
3 (k,s)-Core Computation
4 Fami Decomposition
5 Experimental Evaluation
5.1 Experimental Setting
5.2 Effectiveness
5.3 Efficiency
6 Related Work
7 Conclusion
References
Functional-Oriented Relationship Strength Estimation: From Online Events to Offline Interactions
1 Introduction
2 Problem Formulation
3 Proposed Method
3.1 Simplified Method
3.2 Generalized Role-Aware Latent Function Extraction
3.3 Functional-Aware Relationship Strength Estimation
4 Experiments
4.1 Data Description
4.2 Comparative Methods
4.3 Performance Evaluation
4.4 Model Analysis
5 Related Work
6 Concluding Remarks
References
Incremental and Adaptive Topic Detection over Social Media
1 Introduction
2 Related Work
3 Approach
3.1 Generative Process
3.2 Sampling
3.3 Incremental
3.4 Adaptive Window
4 Evaluation
4.1 Characteristics of Datasets
4.2 Execution Time
4.3 Accuracy
4.4 Qualitative Analysis
5 Conclusion
References
Incorporating User Grouping into Retweeting Behavior Modeling
1 Introduction
2 Overview of System GruBa
2.1 Problem Formulation
2.2 GruBa Framework
3 Feature Extraction
3.1 Basic Feature
3.2 Behavior Feature
3.3 Interest Feature
4 User Clustering
4.1 K-Gru: Clustering in GruBa
4.2 Silhouette Coefficient Metric Computation
5 Group Based Behavior Modeling
6 Performance Evaluation
6.1 Experimental Setting
6.2 Results and Analyses
7 Related Work
8 Conclusions
References
Maximizing Social Influence for the Awareness Threshold Model
1 Introduction
2 Preliminaries
2.1 Problem Definition
2.2 Propagation Models
2.3 Activation Probability
3 Limitations of IC and LT
4 Awareness Threshold (AT)
5 Influence Maximization
6 Scheduled Influence Maximization
6.1 Scheduled Influence Maximization
6.2 Two-Phase Search
6.3 Theoretical Analysis
7 Experiments
7.1 Dataset
7.2 Parameter Setting and Implementation
7.3 Evaluation Results
8 Related Work
8.1 Influence Propagation Model
8.2 Scalable Influence Maximization
9 Conclusion
References
A Time-Aware Path-Based Publish/Subscribe Framework
1 Introduction
2 Problem Statement
2.1 Preliminary Concepts
2.2 Framework Overview
3 Filtering Process
3.1 Time-Aware Location-Based Filter
3.2 Time-Aware Region-Based Filtering
4 Verification Process
5 Experiments
5.1 Experimental Setup
5.2 Experimental Results
6 Related Work
7 Conclusion
References
Direction Recovery in Undirected Social Networks Based on Community Structure and Popularity
1 Introduction
2 The Proposed Model
2.1 Modeling Community Membership with Behavioural Modularity
2.2 Estimating Direction Probability
3 Experimental Evaluation
4 Conclusion
References
Detecting Top-k Active Inter-Community Jumpers in Dynamic Information Networks
1 Introduction
2 Problem Definition
3 Top-k AICJumpers Detection
4 Experiment
5 Conclusion
References
Sequence and Temporal Data Processing
Distributed In-Memory Analytics for Big Temporal Data
1 Introduction
2 Problem Definition
3 Our Solution
3.1 System Framework
3.2 Query Processing
3.3 Implementation on Apache Spark
4 Experiments
4.1 Experiment Setup
4.2 Experimental Results
5 Related Work
6 Conclusion
References
Scalable Active Constrained Clustering for Temporal Data
1 Introduction
2 Problem Formulation
3 Our Proposed Framework
3.1 Constrained Clustering Algorithm
3.2 Active Constraint Selection
3.3 Temporal Smoothness Constraints
4 Experiments
4.1 Constrained Clustering
4.2 Active Constraint Selection
4.3 Temporal Clustering
5 Related Work
6 Conclusion
References
Nearest Subspace with Discriminative Regularization for Time Series Classification
1 Introduction
2 Background and Related Work
2.1 NN-Based Time Series Classification
2.2 Basic Nearest Subspace Algorithm
3 Improved Nearest Subspace Classifier
3.1 ED-Based Regularization
3.2 GEM-Based Regularization
3.3 LFDA-Based Regularization
3.4 Effect of GEM and LFDA-Based Regulation for Improved NS
4 Ensemble NS Classifier
5 Experiments
5.1 Results of NS Classifier with Different Regularization
5.2 Compared with Baselines
5.3 Scalability
6 Conclusions
References
Efficient Approximate Subsequence Matching Using Hybrid Signatures
1 Introduction
2 Preliminaries
3 A Filtering Scheme Using Hybrid Signatures
3.1 Hybrid Signatures
3.2 Candidate Generation Using Hybrid Signatures
4 Experiments
5 Conclusion
References
Trajectory and Streaming Data
MDTK: Bandwidth-Saving Framework for Distributed Top-k Similar Trajectory Query
1 Introduction
2 Related Work
3 Preliminary
3.1 Problem Statement
3.2 Multi-resolution Bounding Envelopes
4 Multi-resolution Based Bounds
4.1 Distance Bounds for Points
4.2 Multi-resolution Based Bounds for Trajectories
5 Implementation of MDTK
5.1 Query Speed Up
5.2 MDTK Processing Framework
5.3 Performance Analysis
6 Experiments
6.1 Experimental Setup
6.2 Efficiency and Scalability of MDTK
7 Conclusion
References
Modeling Travel Behavior Similarity with Trajectory Embedding
1 Introduction
2 Related Work
2.1 User Similarity
2.2 Neural Embedding Representation
3 Preliminaries
3.1 Preliminary Concepts
3.2 The Framework of TEH
4 TEH Model
4.1 Distribution-Based Time Partition
4.2 Trajectory Embedding
4.3 Hash-Based User Similarity Calculation
5 Experiment
5.1 Experimental Setup
5.2 Experimental Results
6 Conclusion
References
MaxBRkNN Queries for Streaming Geo-Data
1 Introduction
2 Related Work
2.1 Facility Location Selection Queries on Static Objects
2.2 Facility Location Selection Queries on Dynamic Objects
3 Problem Formulation
4 Algorithm
4.1 Baseline Algorithm
4.2 Algorithmic Improvements
5 Experimental Evaluation
5.1 Experimental Settings
5.2 Performance Evaluation
6 Conclusion
References
Free-Rider Episode Screening via Dual Partition Model
1 Introduction
2 Related Work
3 Definitions and Problem Statement
4 The EDP Model
4.1 Episode Partition Strategy
4.2 Generate Random Sequences
4.3 Expected Support Definition
4.4 Time Complexity of EDP
5 Expected Support Calculation
5.1 Tracking Minimal Occurrences with Automaton
5.2 The Algorithm
5.3 Time Complexity Analysis
6 Experiments
6.1 Datasets and Experiment Settings
6.2 Results on Data with Known Patterns
6.3 Results on Real-World Dataset
6.4 Scalability
7 Conclusion
References
Maximize Spatial Influence of Facility Bundle Considering Reverse k Nearest Neighbors
1 Introduction
2 Related Work
3 Preliminaries
3.1 Problem Definition
3.2 NP-Hardness
3.3 Baseline Algorithm
4 Techniques
4.1 Solution Overview
4.2 kNN Region
4.3 Inherit Candidate RkNN Set
4.4 Maximum Possible Contribution and Contribution
5 Experiments
6 Conclusion
References
A Road-Aware Neural Network for Multi-step Vehicle Trajectory Prediction
1 Introduction
2 Problem Definition
3 Overview and Preliminaries
3.1 Overview
3.2 Preliminaries
4 Road-Aware Trajectory Prediction
4.1 Intra-road Feature Extraction
4.2 Inter-road Feature Extraction
4.3 Road-Aware Neural Network Prediction Model
5 Experiments
5.1 Experimental Setup
5.2 Results
6 Related Work
7 Conclusion
References
Secure Data Aggregation with Integrity Verification in Wireless Sensor Networks
1 Introduction
2 Related Work
2.1 Secure Aggregation Based on Encryption Mechanism
2.2 Secure Aggregation Based on Unencryption Mechanism
2.3 Related Work on Integrity Verification
3 Problem Statement
3.1 Data SUM Aggregation Model
3.2 Attack Model
3.3 System Goals
4 Our Approach
4.1 Hash-Based Privacy Preserving Mechanism
4.2 Integrity Verification Mechanism
5 Evaluation
5.1 Resistibility Comparison
5.2 Energy Consumption
6 Conclusion
References
A Parallel Spatial Co-location Pattern Mining Approach Based on Ordered Clique Growth
Abstract
1 Introduction
2 Related Work
3 Basic Concepts
4 A Parallel Approach
4.1 Ordered Clique Growth
4.2 An Iterative Parallel Mining Framework
4.3 Parallel Algorithm
5 Experimental Evaluation
5.1 Compared with Serial Mining Methods
5.2 Compared with PCPM_SN
5.3 Scalability Evaluation
6 Conclusions
Acknowledgement
References
RDF and Knowledge Graphs
Multi-query Optimization in Federated RDF Systems
1 Introduction
2 Background
3 Framework
4 Query Decomposition and Source Selection
5 Query Rewriting
5.1 Intuition
5.2 Cost Model
5.3 Query Rewriting Algorithm
6 Local Evaluation and Postprocessing
7 Joining Partial Matches
8 Experimental Evaluation
8.1 Setting
8.2 Evaluation of Proposed Techniques
8.3 Performance Comparison
9 Related Work
10 Conclusion
References
Distributed Efficient Provenance-Aware Regular Path Queries on Large RDF Graphs
1 Introduction
2 Related Work
2.1 Standard Semantics of RPQs
2.2 Provenance-Aware Semantics of RPQs
3 Preliminaries
4 The dProvRPQ Algorithm
4.1 Provenance-Aware RPQs Based on Pregel
4.2 Cycle Detection
5 Optimization Strategies
5.1 Edge Filtering
5.2 Candidate States
5.3 Message Compression
5.4 Message Selection
6 Experimental Evaluation
6.1 Experimental Settings
6.2 Experimental Results
7 Conclusion
References
Discovering Graph Patterns for Fact Checking in Knowledge Graphs
1 Introduction
2 Fact Checking with Graph Patterns
3 Supervised GFC Discovery
4 Discovery Algorithm
4.1 Top-k GFC Mining
4.2 GFC-Based Fact Checking
5 Experimental Study
6 Conclusion
References
KAT: Keywords-to-SPARQL Translation Over RDF Graphs
1 Introduction
2 Preliminaries
3 Keywords-to-SPARQL Translation
3.1 Overview
3.2 Two-Facet Indexing
3.3 Context Aware Ranking
4 Evaluation
4.1 Datasets and Keyword Queries
4.2 Experimental Results
5 Related Work
6 Conclusion
References
Text and Data Mining
A Scalable Framework for Stylometric Analysis of Multi-author Documents
1 Introduction
2 Literature Review
2.1 Stylometry
2.2 Authorship Identification
3 Proposed Solution
3.1 Preprocessing: Feature Extraction
3.2 Preprocessing: Co-Authorship Graph Training
3.3 Multi-authorship Prediction
4 Performance Evaluation
4.1 Experimental Setup
4.2 Experimental Results
5 Conclusions
References
Is a Common Phrase an Entity Mention or Not? Dual Representations for Domain-Specific Named Entity Recognition
1 Introduction
2 Preliminaries and Problem Definition
3 Our Proposed Methodology
3.1 The Proposed Overall Framework
3.2 Specific Domain Knowledge Representation
3.3 General Domain Knowledge Representation
3.4 Sequence Labeling Model
4 Experiments
4.1 Dataset
4.2 Experiment Results and Analysis
5 Related Work
6 Conclusion and Future Work
References
Recognizing Textual Entailment with Attentive Reading and Writing Operations
1 Introduction
2 RTE Architecture
2.1 Refined Reading Module
2.2 Improved Writing Module
3 Experimental Results
3.1 Settings
3.2 Quantitative Results
3.3 Qualitative Analysis
4 Related Works
5 Conclusion
References
Interpreting Fine-Grained Categories from Natural Language Queries of Entity Search
1 Introduction
2 Ranking Model
2.1 Context-Based Category Model
2.2 Topic-Based Category Model
3 Experimental Setup
3.1 Experimental Collection
3.2 Evaluation Metrics
3.3 Parameter Tuning
3.4 Baseline Methods
4 Results and Analysis
4.1 Research Question
4.2 Overall Performance
4.3 Applying Topic-Based Category Model to the Baselines
4.4 Breakdown by Query Subsets
4.5 Impacts of Parameter Settings
5 Related Work
6 Conclusion
References
Improving Short Text Modeling by Two-Level Attention Networks for Sentiment Classification
1 Introduction
2 Related Work
2.1 Deep Neural Networks for Sentiment Classification
2.2 Attention Mechanism
3 The Proposed Model
3.1 Attention-Based Feature Extraction
3.2 Attention-Based Feature Combination
3.3 Sentiment Classification
4 Experiments
4.1 Datasets
4.2 Experimental Settings
4.3 Experiment Results
4.4 Case Study
5 Conclusions
References
Efficient and Scalable Mining of Frequent Subgraphs Using Distributed Graph Processing Systems
1 Introduction
2 Related Work
3 Preliminaries
3.1 Problem Definition
3.2 The gSpan and DFS Code
3.3 Distributed Graph Processing Systems
4 System Overview
4.1 Subgraph Enumeration
4.2 Frequent Subgraph Filter
4.3 Balance the Workload
5 Experimental Evaluation
5.1 Experimental Setup
5.2 Performance Comparison
5.3 Effect of Load Balance
6 Conclusion
References
Efficient Infrequent Itemset Mining Using Depth-First and Top-Down Lattice Traversal
1 Introduction
2 Related Works
3 Preliminaries
4 Negative Infrequent Itemset Tree Miner
5 Experimental Evaluation
6 Conclusion and Future Works
References
Online Subset Topic Modeling for Interactive Documents Exploration
1 Introduction
2 Related Works
3 Subset Topic Modeling
3.1 Proposed Algorithm
4 Experiments
4.1 Perplexity
4.2 Efficiency
5 Conclusion
References
Main Point Generator: Summarizing with a Focus
1 Introduction
2 Related Work
3 Main Pointer Generator Network Model
3.1 Encoding
3.2 Decoding
3.3 Training
4 Experiments and Results
4.1 Model Parameters and Optimization
4.2 Dataset and Evaluation
4.3 Results
5 Conclusion
References
Correction to: Database Systems for Advanced Applications
Correction to: J. Pei et al. (Eds.): Database Systems for Advanced Applications, LNCS 10827, https://doi.org/10.1007/978-3-319-91452-7
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