Knowledge Management and Acquisition for Intelligent Systems: 15th Pacific Rim Knowledge Acquisition Workshop, PKAW 2018, Nanjing, China, August 28-29, 2018, Proceedings.

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Bibliographic Details
Authors and Corporations:	Yoshida, Kenichi, Lee, Maria
Other Authors:	Lee, Maria. []
Edition:	1st ed.
Type of Resource:	E-Book
Language:	English
published:	Cham : Springer International Publishing AG, 2018. ©2018.
Series:	Lecture Notes in Computer Science Series
Subjects:	Knowledge acquisition (Expert systems)-Congresses. Electronic books.
Source:	Ebook Central
ISBN:	9783319972893

Table of Contents:

Intro
Preface
Organization
Contents
Building a Commonsense Knowledge Base for a Collaborative Storytelling Agent
Abstract
1 Introduction
2 Related Works
3 Extracting Knowledge from ConceptNet
4 Expanding the Commonsense Ontology
5 Filtering the Concepts
6 Discussion
6.1 Processing User Input
6.2 Generating Responses
7 Conclusion and Further Work
References
A Knowledge Acquisition Method for Event Extraction and Coding Based on Deep Patterns
1 Introduction
2 Event Extraction and Coding Framework
2.1 AfPak Ontology
2.2 Event Definition and Structure
2.3 Pattern Creation and Generalisation
2.4 Pattern Based Event Extraction
3 Event Coding Assistant
4 Evaluation
4.1 Evaluation of Event Coding
4.2 Evaluation of Pattern Generalisation
5 Related Work
6 Conclusions and Future Research
References
Incremental Acquisition of Values to Deal with Cybersecurity Ethical Dilemmas
Abstract
1 Introduction
2 Background and Theoretical Foundations
2.1 Schwartz's Values Theory
2.2 AORTA
2.3 Adding Values to BDI Agents
2.4 Ripple Down Rules
3 Proposed Approach
4 Example
5 Discussion
6 Conclusion
References
Towards Realtime Adaptation: Uncovering User Models from Experimental Data
Abstract
1 Introduction
2 Identifying Data for Building User Models
3 Methodology
3.1 Intelligent Virtual Agents for Reducing Study Stress
3.2 Educational Virtual World for Science Inquiry
3.3 Data Processing and Analysis
4 Results
4.1 Reducing Study Stress Results
4.2 Educational Virtual World Results
5 Discussion
6 Conclusions and Future Directions
Acknowledgements
References
Supporting Relevance Feedback with Concept Learning for Semantic Information Retrieval in Large OWL Knowledge Base
Abstract
1 Introduction.
2 Related Work
3 Concept Learning Problem in OWL Knowledge Base
3.1 Concept Learning Problem
3.2 The General Procedure of CLDL Based Interactive Search
4 Improving CLDL Search Performance by Reducing the Scale of OWL Knowledge Base
4.1 Reducing the Scale of CLDL Problem
4.2 Clustering Based Partition by Analyzing the Structure of Knowledge Base
4.2.1 Analyzing the Cluster Structure of OWL Knowledge Base
4.2.2 Partitioning OWL Knowledge Base by Clustering
5 Experiment
5.1 Dataset and Evaluation Criteria
5.2 Experiment Results
5.2.1 The CLDL Based Search on the Complete Knowledge Base
5.2.2 The Search Based on Partitioned Knowledge Base
6 Conclusion and Further Work
Acknowledgement
References
Combining Concept Learning and Probabilistic Information Retrieval Model to Understand User's Searching Intent in OWL Knowledge Base
Abstract
1 Introduction
2 Related Work
3 Concept Learning and Probabilistic Information Retrieval
4 Probabilistic IR in OWL KB Using Concept Learning
5 Experiment
5.1 Describing User's Intent
5.2 Efficiency of Uncertain Inference in OWL KB for Probabilistic IR
5.3 Overall Performance of the IR Prototype Designed
6 Conclusion
Acknowledgement
References
Diabetic Retinopathy Classification Using C4.5
Abstract
1 Introduction
2 Material
3 Methods
3.1 Preprocessing
3.2 Segmentation of MA Candidates
3.3 Feature Space
3.4 Generation of Classification Rules
4 Results
5 Conclusions
References
Stock Price Movement Prediction from Financial News with Deep Learning and Knowledge Graph Embedding
Abstract
1 Introduction
2 Related Work
2.1 Deep Learning in Stock Market Prediction
2.2 Knowledge Graph Embedding
2.3 Representation Learning Based on Text and Knowledge
3 Task Description.
3.1 Research Architecture
3.2 Dataset Description
3.3 Data Pre-Processing
4 Methodology
4.1 Feature Selection by the Model of Joint Learning
4.1.1 Feature Extraction from the News Title Using CNN Model
4.1.2 Feature Extraction from the Event Tuple Using TransE Model
4.1.3 Combined Loss Function for Feature Extraction
4.2 Stock Market Prediction Model
4.2.1 Long Short-Term Memory Networks
4.2.2 Output Layer
5 Experiment and Results
5.1 Experiment Settings
5.2 Results and Discussion
6 Conclusions and Future Works
Acknowledgments
References
Sample Dropout for Audio Scene Classification Using Multi-scale Dense Connected Convolutional Neural Network
1 Introduction
2 Related Work
3 Audio Scene Classification Datasets and Experimental Setup
4 Multi-scale DenseNet
5 Culling Training Samples for Convolutional Neural Network
6 Experimental Results
7 Conclusion
References
LOUGA: Learning Planning Operators Using Genetic Algorithms
1 Introduction
2 Background and Problem Specification
3 LOUGA
3.1 Genome Model
3.2 Pre-processing
3.3 Fitness Function
3.4 The Genetic Algorithm
3.5 Learning Effects Predicate by Predicate
3.6 Learning Preconditions
4 Results of Experiments
4.1 Efficiency of Predicate by Predicate Approach
4.2 Comparison of GA and Hill Climbing
4.3 Efficiency of Using Types
4.4 Comparison to ARMS
5 Conclusions
References
k-NN Based Forecast of Short-Term Foreign Exchange Rates
1 Introduction
2 Forecasting Exchange Rates Using k-NN
3 Proposed Method
4 Experimental Settings
4.1 Datasets
4.2 Baseline Methods
4.3 Evaluation Metrics
4.4 Experimental Method for Exchange Rate Forecast
4.5 Experimental Method for Pseudo-Trading
5 Experimental Results
5.1 Evaluation in Forecasting Exchange Rates.
5.2 Evaluation via Pseudo-Trading
6 Conclusion
References
Multi-dimensional Banded Pattern Mining
1 Introduction
2 Related Work
3 BPM Formalism
4 Calculation of Banding Scores
5 Banded Pattern Mining
5.1 Generation of the Set Max
6 Evaluation
6.1 Comparison of BPM Algorithms (ABPM and EBPM)
6.2 Comparison with Previous Work (BC and MBA)
7 Conclusion
References
Automated Business Process Discovery and Analysis for the International Higher Education Industry
Abstract
1 Introduction
2 Background
3 Process Mining Overview
3.1 Business Process Management
3.2 Process Mining
3.3 Event Logs
3.4 Types of Process Mining
3.5 Process Mining Methodology Framework
4 Process Mining Knowledge Generation
4.1 Event Log Extraction
4.2 Event Log Preparation
4.3 Automated Business Process Discovery
5 Discussion
6 Conclusion
References
An Analysis of Interaction Between Users and Open Government Data Portals in Data Acquisition Process
Abstract
1 Introduction
2 Theoretical Foundation
2.1 Open Government Data Portal
2.2 Users of Open Government Data Portal
2.3 Technology Acceptance Model
3 Research Design and Methods
4 Results
4.1 Users' Data Acquisition Method
4.2 Users' Need of Data Quality
4.3 Helping Functions
5 Discussion
6 Conclusion
References
Blockchain: Trends and Future
1 Introduction
2 Blockchain Basics
3 Trends in Blockchain Type Data Structure
4 Trends in Consensus Algorithms
5 Trends in Blockchain Systems
6 Blockchain-Based Internet and Its Challenges
7 Conclusion
References
Selective Comprehension for Referring Expression by Prebuilt Entity Dictionary with Modular Networks
1 Introduction
2 Related Work
3 Our Model
3.1 Expression Filtering Model
3.2 Expression Parsing Module.
3.3 Localization Module
4 Experiments
4.1 Add Error Expression
4.2 The Evaluation on Google-Ref Dataset
4.3 The Evaluation on Visual-7W
5 Conclusion
References
Pose Specification Based Online Person Identification
1 Introduction
2 Related Work
3 Our Method
3.1 Pose Prediction and Recognition System
3.2 PSM and LSTM
3.3 Face, Character and Clothes Recognition
4 Experiment
4.1 Soccer Dataset
4.2 Results and Analysis
5 Conclusion
References
Get the Whole Action Event by Action Stage Classification
1 Introduction
2 Related Work
2.1 Off-line Methods
2.2 On-line Methods
3 Our Model
3.1 Online Action Tube Generation
3.2 Classifying the Action Stage
3.3 Link Conditions of Two Action Tubes
4 Implementation
5 Experiments
5.1 Dataset:UCF-24
5.2 Implementation Details
5.3 Validation of Action Stage Classification
5.4 Complete Action Tube Generation Performance
5.5 Comparison with the Existing Methods
6 Conclusion and Future Works
References
Clothing Attribute Extraction Using Convolutional Neural Networks
Abstract
1 Introduction
2 Related Work
2.1 Semantic Annotation of Images
2.2 Clothing Attributes Extraction from Images
2.3 Clothing Attribute Extraction by CNN
3 Method
3.1 Feature Extraction
3.2 SIFT
3.3 Texture Description
3.4 Color Description
3.5 Skin Probability
3.6 Convolution Layer
3.7 Clothing Attribute Classifier
4 Experiments
5 Results
6 Conclusion
References
Research Paper Recommender Systems on Big Scholarly Data
Abstract
1 Introduction
2 Current Status of Research Paper Recommender Systems
2.1 Research Paper Recommender Systems Related Studies
2.2 Research Paper Recommender Systems from the Perspective of Big Scholarly Data.
2.3 Public Available Big Scholarly Datasets.