Intelligent Information and Database Systems 11th Asian Conference, ACIIDS 2019, Yogyakarta, Indonesia, April 8-11, 2019, Proceedings, Part I

• Main Authors: Nguyen, Ngoc Thanh, Gaol, Ford Lumban, Hong, Tzung-Pei, Trawiński, Bogdan
• Format: eBook
• Language: English
• Published: Cham Springer International Publishing AG 2019
• Edition: 1
• Subjects: Artificial intelligence
• ISBN: 9783030147983; 3030147983

Table of Contents:

• 5 Conclusions and Future Work -- Acknowledgments -- References -- Text Processing and Information Retrieval -- Robust Web Data Extraction Based on Unsupervised Visual Validation -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Web Data Extraction as a Classification Problem -- 3.2 Visual Validation -- 4 Methodology -- 4.1 Selection -- 4.2 Visual Validation -- 5 Experimental Setup -- 5.1 Dataset -- 5.2 Selection -- 5.3 Visual Validation -- 5.4 Tools and Implementation -- 6 Experimental Evaluation -- 6.1 Training Classifiers -- 6.2 Comparing SEL and SEL+VV -- 6.3 Comparing SEL+ and SEL+VV+ and Classification to VV -- 7 Conclusion -- References -- A Character-Level Deep Lifelong Learning Model for Named Entity Recognition in Vietnamese Text -- Abstract -- 1 Introduction -- 2 Bidirectional Long Short-Term Memory (Bi-LSTM) with a CRFs Layer -- 2.1 Bidirectional LSTM (Bi-LSTM) -- 2.2 Bi-LSTM+CRF -- 3 The Proposed Character-Level Deep Lifelong Learning Model -- 3.1 Training Model -- 3.2 Lifelong Prefix Feature Extraction -- 3.3 Evaluating Model -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Experiment Setting -- 4.3 Experiment Results and Analysis -- 5 Related Works -- 6 Conclusions and Future Work -- Acknowledgments -- References -- Identification of Conclusive Association Entities by Biomedical Association Mining -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Article Indexing by Biomedical Terms -- 2.2 Extraction of Biomedical Entity Associations -- 2.3 Estimation of Entity-Article Relatedness -- 2.4 Prediction of New Associations by Existing Associations -- 3 Association Mining to Improve CAE Identification -- 4 Empirical Evaluation -- 4.1 Basic Experimental Settings -- 4.2 Baselines and Evaluation Criteria -- 4.3 Results -- 5 Conclusion and Future Extension -- Acknowledgment -- References
• 3.3 Causality Rule Construction -- 3.4 Event Prediction -- 4 Context-Aware Event Prediction -- 5 Experiments -- 5.1 Environment Settings -- 5.2 Results -- 6 Conclusion -- References -- A Method for Detecting and Analyzing the Sentiment of Tweets Containing Conditional Sentences -- 1 Introduction -- 2 Related Works -- 3 Research Problems -- 4 The Proposed Method -- 4.1 Features Selection -- 4.2 Detecting Tweets Containing the Conditional Sentence -- 4.3 Sentiment Analysis of Tweets Containing Conditional Sentence -- 5 Experiment -- 5.1 Data Acquisition -- 5.2 Evaluation Results -- 5.3 Results and Discussion -- 6 Conclusion and Future Work -- References -- Aggregating Web Search Results -- 1 Introduction -- 1.1 Search Engine Results Page -- 1.2 Metasearch - The Aggregation of SERPs -- 1.3 Related Works -- 2 Method and Experiment -- 2.1 Aggregation -- 2.2 Measures -- 2.3 Queries -- 2.4 Relevance Assessment -- 3 Results -- 3.1 Statistical Significance -- 4 Conclusions -- References -- Cross-Lingual Korean Speech-to-Text Summarization -- 1 Introduction -- 2 Related Work -- 3 Cross-Lingual Speech-to Text Summarization Method -- 3.1 Speech-to-Text Translation -- 3.2 Sentence Clustering -- 3.3 Summary Sentence Generation -- 4 Experiment -- 4.1 Dataset -- 4.2 Evaluation -- 4.3 Results and Discussions -- 5 Conclusion and Future Work -- References -- On Some Approach to Evaluation in Personalized Document Retrieval Systems -- 1 Introduction -- 2 Related Works -- 2.1 Ontology-Based User Profile -- 2.2 Distance Between Bayesian Networks -- 3 Personalized Document Retrieval Model -- 3.1 Domain Ontology -- 3.2 User Profile -- 4 Algorithm for Determining Representative Profile for a Group of Users -- 5 Experimental Evaluations -- 5.1 Methodology of Simulations -- 5.2 Quality Condition -- 5.3 Obtained Results -- 6 Summary -- References
• Machine Learning and Data Mining
• Term Rewriting that Preserves Models in KR-Logic -- 1 Introduction -- 2 An Introductory Example -- 2.1 Example: Proof Problem in Group Theory -- 2.2 Example: Usual Proof by Rewriting Terms -- 2.3 Example: Formalization with Formulas in the First-Order Logic -- 2.4 Inappropriateness of Formalization in the First-Order Logic -- 2.5 A Logical Problem Solving Method -- 3 Representation in KR-Logic -- 3.1 Alphabet and Terms of KR-Logic -- 3.2 Atoms and WFFs -- 3.3 Example: Formalization with Formulas in KR-Logic -- 4 A Canonical Logical Structure in KR-Logic -- 4.1 Extended Clauses in KR-Logic -- 4.2 Example: Formalization in Clausal Form in KR-Logic -- 4.3 A Canonical Logical Structure of Extended Clauses -- 5 Term Rewriting Rules -- 5.1 Term Contexts, Atom Contexts, and Clause Contexts -- 5.2 Conditional Term Rewriting Rules -- 5.3 Example: Term Rewriting Rules for the Sample Problem -- 6 Term Rewriting that Preserves Models -- 6.1 Model-Preservation Theorem -- 6.2 Example: Model-Preserving Rewriting for the Sample Problem -- 7 Conclusion -- References -- Towards Knowledge Formalization and Sharing in a Cognitive Vision Platform for Hazard Control (CVP-HC) -- Abstract -- 1 Introduction -- 2 Cognitive Systems -- 3 Knowledge Engineering -- 3.1 Knowledge Acquisition -- 3.2 Knowledge Formalism -- 4 Communication System for Knowledge Sharing -- 4.1 Real Time Publisher/Subscriber Communication Model -- 5 CVP-HC -- 5.1 Message Configuration -- 5.2 Communication Model Structure -- 6 Conclusions -- References -- Assessing Individuals Learning's Impairments from a Social Entropic Perspective -- Abstract -- 1 Introduction -- 2 Fundamentals -- 2.1 Knowledge Representation and Argumentation -- 2.2 Evaluating a Qualitative Data Item in Terms of Its Quantitative Complement -- 3 Case Study -- 3.1 Objectives -- 3.2 Feature Extraction -- 4 Computational Model
• Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Knowledge Engineering and Semantic Web -- Algorithms for Merging Probabilistic Knowledge Bases -- Abstract -- 1 Introduction -- 2 Probabilistic Knowledge Bases -- 3 Probabilistic Merging Operators -- 3.1 Mean Merging Operator (MMO) ⊕ -- 3.2 Coefficient Mean Merging Operator (CMMO) ⊖ -- 4 Proposed Merging Algorithms for PKB -- 4.1 Algorithms -- 4.2 The Computational Complexity -- 5 Conclusion -- Acknowledgment -- References -- A Formal Framework for the Ontology Evolution -- 1 Introduction -- 2 Related Works -- 3 Basic Notions -- 4 Tracking Changes During Ontology Evolution -- 4.1 Level of Concepts -- 4.2 Level of Instances -- 4.3 Level of Concepts' Relations -- 4.4 Level of Instances' Relations -- 4.5 Ontology Change Log -- 5 Illustration of the Ontology Evolution -- 6 Future Works and Summary -- References -- Logical Problem Solving Framework -- 1 Introduction -- 2 Logical Problem Solving Framework -- 2.1 Canonical Logical Structures and Basic Related Concepts -- 2.2 Model-Intersection Problems -- 2.3 Answer Mappings -- 2.4 ET Steps and ET Rules -- 2.5 Control -- 2.6 Logical Problem Solving Framework -- 2.7 Solution Methods Based on LPSF -- 3 Experiments -- 3.1 Agatha Puzzle -- 3.2 Formalization by First-Order Formulas -- 3.3 Meaning-Preserving Skolemization -- 3.4 Computation Control with Prioritized ET Rules -- 3.5 ET Rules and Computation Control for Agatha Problems -- 3.6 Solution of Agatha QA Problem -- 3.7 Solution of Agatha Proof Problem -- 3.8 Failures of Conventional Methods -- 4 Canonical Logical Structure in KR-Logic -- 4.1 Alphabet of KR-Logic -- 4.2 Terms and Atoms -- 4.3 Extended Clauses -- 4.4 Constraints for Function Variables -- 4.5 Canonical Logical Structure -- 5 Improvement of Logical Problem Solving -- 6 Conclusions -- References
• A Data Preprocessing Method to Classify and Summarize Aspect-Based Opinions Using Deep Learning -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Data Preprocessing Model -- 3.2 Opinion Summarization -- 4 Experimental Results -- 4.1 Corpus -- 4.2 Proposed System Configuration -- 4.3 Experiments -- 5 Conclusion -- Acknowledgments -- References -- Word Mover's Distance for Agglomerative Short Text Clustering -- 1 Introduction -- 2 Related Work -- 3 Word Mover's Distance -- 4 Clustering Method -- 4.1 Initial Preprocessing -- 4.2 WMD Clustering -- 4.3 Refining Cluster Selection -- 5 Experiments -- 5.1 Cluster Evaluation -- 5.2 Qualitative Analysis -- 6 Conclusion -- References -- Improving Semantic Relation Extraction System with Compositional Dependency Unit on Enriched Shortest Dependency Path -- 1 Introduction -- 2 Related Work -- 3 Enriched Shortest Dependency Path -- 3.1 Dependency Tree and Shortest Dependency Path -- 3.2 Dependency Tree Normalization -- 3.3 The Dependency Unit on the SDP -- 4 Proposed Model -- 4.1 Compositional Embeddings -- 4.2 CNN with Dependency Unit -- 4.3 Classification -- 4.4 Objective Function and Learning Method -- 5 Experimental Evaluation -- 5.1 Dataset -- 5.2 Experimental Results and Discussion -- 6 Conclusion -- References -- An Adversarial Learning and Canonical Correlation Analysis Based Cross-Modal Retrieval Model -- 1 Introduction -- 2 ALCCA-CMR Model -- 2.1 Problem Formulation -- 2.2 Proposed Framework -- 2.3 Adversarial Learning and CCA -- 2.4 Cross-Modal Retrieval -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Experimental Results -- 4 Related Work -- 5 Conclusion and Future Work -- References -- Event Prediction Based on Causality Reasoning -- 1 Introduction -- 2 Preliminary -- 3 Survey of Causality Based Event Prediction -- 3.1 Framework -- 3.2 Event Representation