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Intro; Preface; Organization; Contents; The 14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2019); A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045; 1 Introduction; 2 Security Target and Its Evaluation Process; 2.1 Security Target with ISO/IEC 15408; 2.2 Evaluation Process Based on ISO/IEC 18045; 2.3 Issues of the Evaluation Process; 3 Supporting Methods for Evaluation on Security Targets; 3.1 Analysis of Evaluation Tasks on Security Targets; 3.2 Supporting Methods
4 Security Target Evaluator: A Supporting Tool for Evaluation on Security Targets4.1 Requirements for Security Target Evaluator; 4.2 Components for Supporting Methods in Security Target Evaluator; 4.3 Management of Relevant Documents and Data; 5 Concluding Remarks; References; An Investigation on Multi View Based User Behavior Towards Spam Detection in Social Networks; Abstract; 1 Introduction; 2 Related Work; 3 Hypothesis; 4 Approach and Experimental Setup; 4.1 Dataset Description; 4.2 Representation of User's Content Interest for the Investigation
4.3 Representation of User's Popularity for the Investigation4.4 Experimental Methods for User Behavior Analysis; 5 Discussion; 6 Conclusion; References; A Cluster Ensemble Strategy for Asian Handicap Betting; 1 Introduction; 2 Related Works; 3 Methodology; 3.1 Expected Goal Difference Trend; 3.2 Model Design; 3.3 Component Cluster; 3.4 Cluster Ensemble; 4 Case Studies; 4.1 Data; 4.2 Evaluation Metrics; 4.3 Model Parameters Selection; 4.4 Out of Sample Prediction; 5 Conclusions; References; Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example; Abstract
1 Introduction2 Literature Review; 3 Method; 3.1 Discovery; 3.2 Understanding; 3.3 Implementation; 3.3.1 Query Service; 3.3.2 Crime Information Analysis; 3.3.3 Applied System Q 3.3.4 Image Analysis Service; 3.3.5 Real-Time Video and Image Transmission; 3.3.6 Internet Information Collection; 4 Discussion and Future Work; 5 Conclusion; References; Early Churn User Classification in Social Networking Service Using Attention-Based Long Short-Term Memory; 1 Introduction; 2 Data; 2.1 RoomClip; 2.2 Definition of Early Churn Users in RoomClip; 2.3 Distribution of Event Interval of New Users
3 Proposed Model3.1 Input; 3.2 Sequence Encoding Layer; 3.3 Attention Layer; 3.4 Early Churn Classification Layer; 3.5 Learning Algorithm; 4 Experiment; 4.1 Evaluation Criteria; 4.2 Preprocessing; 4.3 Baseline Models; 4.4 Result; 5 Feature Importance Analysis; 5.1 Importance of Each Temporal Part in Event Sequence; 5.2 Importance of Event Type; 6 Related Research; 7 Discussion and Conclusion; References; PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019); Weakly Supervised Learning by a Confusion Matrix of Contexts; Abstract; 1 Introduction
4 Security Target Evaluator: A Supporting Tool for Evaluation on Security Targets4.1 Requirements for Security Target Evaluator; 4.2 Components for Supporting Methods in Security Target Evaluator; 4.3 Management of Relevant Documents and Data; 5 Concluding Remarks; References; An Investigation on Multi View Based User Behavior Towards Spam Detection in Social Networks; Abstract; 1 Introduction; 2 Related Work; 3 Hypothesis; 4 Approach and Experimental Setup; 4.1 Dataset Description; 4.2 Representation of User's Content Interest for the Investigation
4.3 Representation of User's Popularity for the Investigation4.4 Experimental Methods for User Behavior Analysis; 5 Discussion; 6 Conclusion; References; A Cluster Ensemble Strategy for Asian Handicap Betting; 1 Introduction; 2 Related Works; 3 Methodology; 3.1 Expected Goal Difference Trend; 3.2 Model Design; 3.3 Component Cluster; 3.4 Cluster Ensemble; 4 Case Studies; 4.1 Data; 4.2 Evaluation Metrics; 4.3 Model Parameters Selection; 4.4 Out of Sample Prediction; 5 Conclusions; References; Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example; Abstract
1 Introduction2 Literature Review; 3 Method; 3.1 Discovery; 3.2 Understanding; 3.3 Implementation; 3.3.1 Query Service; 3.3.2 Crime Information Analysis; 3.3.3 Applied System Q 3.3.4 Image Analysis Service; 3.3.5 Real-Time Video and Image Transmission; 3.3.6 Internet Information Collection; 4 Discussion and Future Work; 5 Conclusion; References; Early Churn User Classification in Social Networking Service Using Attention-Based Long Short-Term Memory; 1 Introduction; 2 Data; 2.1 RoomClip; 2.2 Definition of Early Churn Users in RoomClip; 2.3 Distribution of Event Interval of New Users
3 Proposed Model3.1 Input; 3.2 Sequence Encoding Layer; 3.3 Attention Layer; 3.4 Early Churn Classification Layer; 3.5 Learning Algorithm; 4 Experiment; 4.1 Evaluation Criteria; 4.2 Preprocessing; 4.3 Baseline Models; 4.4 Result; 5 Feature Importance Analysis; 5.1 Importance of Each Temporal Part in Event Sequence; 5.2 Importance of Event Type; 6 Related Research; 7 Discussion and Conclusion; References; PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019); Weakly Supervised Learning by a Confusion Matrix of Contexts; Abstract; 1 Introduction