Mining Intelligence and Knowledge Exploration: 7th International Conference, MIKE 2019, Goa, India, December 19–22, 2019, Proceedings

Preface
Organization
Contents
On the Differences Between Human Agents and Logic-Based Software Agents Discourse Understanding
1 Interpretation Models in First Order Logic
2 Reducing the Interpretation Models of the Logical Agent
3 When More Models Are Better?
4 Discussion and Related Work
5 Conclusion
References
A Study on the Importance of Linguistic Suffixes in Maithili POS Tagger Development
1 Introduction
2 Related Work
3 Maithili POS Tagger Development Using CRF
3.1 Training Data
3.2 CRF Model Creation
3.3 Accuracy of CRF Based System
3.4 Discussions
4 Morphological Analysis for Improving Maithili POS Tagger
4.1 Inflections in Maithili Words
4.2 Accuracy with Morphological Suffixes
5 Conclusion
References
Text Cohesion in CQA - Does It Impact Rating?
1 Introduction
2 Approach
3 Survey Results and Analysis
4 Conclusion
References
Person Name Segmentation with Deep Neural Networks
1 Introduction
2 Related Work
3 Problem Formulation
4 Proposed Approach
4.1 RNN-Based Segmenter
4.2 HMM-Based Segmenter
5 Experiments and Results
5.1 Dataset
5.2 Results
5.3 Visualization of the Learned Representations
6 Conclusion
References
Convex vs Convex-Concave Objective for Rare Label Classification
1 Introduction
2 Relatedwork
3 Approach
3.1 Graph Based Semi-supervised Learning for Binary Classification
3.2 KL-Divergence Based SSL
4 Experiments
4.1 Datasets
4.2 Results
5 Conclusion
References
Skew Aware Partitioning Techniques for Multi-way Spatial Join
1 Introduction
2 Spatial Join
3 Multi-way Spatial Join Techniques
3.1 Controlled-Replicate
3.2 SLC
3.3 BSP-Binary Split Partition Method
4 Results and Discussion
5 Conclusion and Future Work
References
The Relationship Between Sentiments of Social Media and Economic Indicators
1 Introduction
2 Related Work
2.1 The Relevant Indices of the Happiness Index
2.2 Sentiment Analysis
3 Research Methodology
3.1 Research Method
3.2 Data Collection
3.3 Calculation of Emotion Scores
4 Research Results
4.1 The Relationship Between Happiness Index and Forum Sentiment
4.2 The Relationship Between GDP Annual Rate of Increase and the Forum Sentiment
4.3 The Relationship Between GNI Annual Rate of Increase and the Forum Sentiment
5 Conclusion and Future Research
References
Entity and Verb Semantic Role Labelling for Tamil Biomedicine
1 Introduction
2 Related Works
3 SRL for Tamil Biomedical Texts
3.1 Domain-Specific Verb Semantic Roles
3.2 Feature Engineering and Verb Frame Extraction
3.3 Maximum Entropy Based Training Model
4 Experiments and Results
4.1 Dataset
4.2 Dependency Parse Tree
4.3 Experimental Setup
4.4 Combined Results and Discussion
5 Conclusion
References
Exploring Chinese Dynamic Sentiment/Emotion Analysis with Text Mining—Taiwanese Popular Movie Reviews Comment as a Case
1 Introduction
2 Related Work
2.1 Sentiment and Emotion Analysis
3 Research Methodology
3.1 Data Collection
3.2 Pre-processing
3.3 Verification of Authenticity of the Review Content
3.4 Sentiment and Emotion Time Dynamic Analysis
4 Research Results
4.1 Data Collection
4.2 Pre-processing
4.3 Verification of the Authenticity of the Review Content
4.4 Sentiment and Emotional Time Dynamic Analysis
5 Conclusion and Future Research
References
Detection of Misbehaviors in Clone Identities on Online Social Networks
1 Introduction
2 Related Work
3 Data Collection and Ground Truth
4 Proposed Approach
5 Evaluation and Results
6 Limitations and Future Work
7 Conclusion
References
Contextual Predictability of Texts for Texts Processing and Understanding
1 Introduction
2 Related Work
2.1 General Approaches to Analyzing Contextual Predictability
2.2 Contextual Predictability Analysis via Cloze-Test
2.3 Statistical Models for Contextual Predictability
3 Data
4 Text Model Construction
5 Results Discussion
6 Conclusion
References
Haralick Features from Wavelet Domain in Recognizing Fingerprints Using Neural Network
1 Introduction
2 Feature Extraction
2.1 Wavelet Transform
2.2 GLCM
2.3 Wavelet Co-occurrence Features
3 Feedforward Neural Network
4 Training Algorithm
5 Results and Discussion
6 Conclusion
References
Circular Local Directional Pattern for Texture Analysis
1 Introduction
2 Features Methods for Texture Analysis
2.1 Local Binary Pattern
2.2 Local Directional Pattern
2.3 Circular Local Directional Pattern
3 Experimental Results and Discussion
3.1 Image Dataset
3.2 Classification Evaluation
3.3 Results Discussion
4 Conclusion
References
A Deep Learning Approach for Automatic Segmentation of Dental Images
1 Introduction
2 Related Work
3 Methods and Techniques
3.1 Data Augmentation
3.2 Pre-processing
3.3 Classification
4 Experimental Results and Discussion
5 Conclusion
References
Quality Assessment of Fingerprint Images Using Local Texture Descriptors
1 Introduction
2 Proposed Method
2.1 Weber Local Descriptors
2.2 Binarized Statistical Image Features:
2.3 Support Vector Machine
3 Experimental Results
3.1 Block Texture Quality Assessment
3.2 Fingerprint Texture Quality Assessment
4 Conclusion
References
Skeletal Age Estimation from Hand Radiographs Using Transfer Learning
1 Introduction
2 Transfer Learning
3 Ensemble Learning
3.1 Averaging
3.2 Weighted Average
4 Methodology
4.1 Dataset
4.2 Evaluation Protocols
5 Results
6 Conclusion
References
Fractal Geometry for Early Detection and Histopathological Analysis of Oral Cancer
1 Introduction
2 Materials and Methods
2.1 Dataset Used
2.2 Proposed Model
3 Results and Discussion
3.1 Extraction of Morphological Feature in Terms of Fractal Dimension
3.2 Improvement in Clinical Interpretation Using the Fractal Dimension
4 Conclusion
References
Under-Sample Binary Data Using CURE for Classification
1 Introduction
2 CURE
2.1 Algorithm
3 Experimental Results and Discussion
3.1 Datasets
4 Conclusion
References
Extraction of White and Grey Lesion Features for the Inference of ADHD
1 Introduction
2 Methodology
2.1 MRI Image Acquisition
2.2 Skull Stripping
2.3 Region Filling
2.4 Gray and White Lesions Extraction
2.5 Feature Extraction
3 Experimental Results
4 Conclusion
References
Skin Lesion Segmentation Techniques Based on Markov Random Field
1 Introduction
2 Techniques Based on MRF
2.1 MRF Model
2.2 Pixel-Based MRF Model
2.3 Region-Based MRF Model
2.4 Edge-Based MRF Model
2.5 (Pixel, Region)-Based MRF Model
2.6 (Pixel, Region, Edge)-Based MRF Model
2.7 Parameters Setting
3 Performance Analysis
3.1 Data Sets
3.2 Evaluation Metric Calculation
3.3 Performance Evaluation Analysis
4 Conclusion
References
Performance of Coronary Plaque Feature Extraction and Identification of Plaque Severity for Intravascular Ultrasound B-Mode Images
1 Introduction
2 Materials and Methods
2.1 IVUS Image Data Acquisition
2.2 Adjacent Pattern – Feature Extraction
2.3 SVM Based CNN Classifier
3 Results and Discussion
3.1 Performance Measure for Classification
4 Conclusion
References
Identification of Palatal Fricative Fronting Using Shannon Entropy of Spectrogram
1 Introduction
2 Motivation
3 Literature Review
4 Speech Dataset
5 Methodology
5.1 Automatic Segmentation of /s/ and /sh/
5.2 Feature Extraction
5.3 Classification Using Support Vector Machine (SVM)
6 Results and Discussion
7 Summary and Conclusion
References
Identification of Nasalization and Nasal Assimilation from Children's Speech
1 Introduction
2 Motivation
3 Literature Review
4 Methodology
4.1 Speech Dataset
4.2 Preprocessing
4.3 Feature Extraction
4.4 Feature Comparison and Decision Making
4.5 Reference Template Selection
4.6 Identification of Nasalization
5 Results and Discussion
6 Summary and Conclusion
References
Kannada Dialect Classification Using CNN
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Dataset Details
3.2 Feature Extraction
3.3 Convolutional Neural Network
4 Results and Discussion
5 Conclusion
References
Robust Handwritten Digit Classification Using Tensors Decomposition
1 Introduction
2 RASL: Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images
3 The Proposed Robust Tensor (RTensor)
3.1 Similarity Measure for Digit Classification
4 Experiments
4.1 Experimental Setting
4.2 Recognition Performance
4.3 Alignment Performance
4.4 Runtime Performance
5 Conclusion
References
Clustering of Interval Valued Data Through Interval Valued Feature Selection: Filter Based Approaches
1 Introduction
2 Background
3 Interval Valued Feature Selection
3.1 Transformation Based Approaches
3.2 Feature Clustering Based Approaches
4 Experimentation and Results
4.1 Datasets
4.2 Experimental Setup
4.3 Results
5 Comparative Analysis
6 Conclusion
References
Frequent Itemsets Based Partitioning Approach to Decision Tree Classifier
1 Introduction
2 Related Works
3 Frequent Itemsets Based Partitioning Decision Tree Technique (FIPDT)
3.1 Algorithm
4 Experimental Analysis
4.1 Structural Instability
4.2 Statistical Tests
5 Conclusions
References
Investigating Fingerprint Quality Features for Liveness Detection
1 Introduction
2 Related Works
3 Proposed Method
3.1 Quality Feature Extraction
3.2 Feature Scaling
3.3 Feature Selection
4 Experimental Results
4.1 Evaluation Results by Various Classifiers
4.2 Quality Features Performance
4.3 Performance Improvement with Quality Features
4.4 Comparative Analysis
5 Conclusion
References
Full Informed Digital Transformation Simpler, Maybe Better
1 Introduction
2 Fundamentals
3 Case Study
3.1 Digital Maturity Assessment
3.2 The Possible Role of an EU Body in the Future EU Cybersecurity Landscape
3.3 Computational Make-Up
4 Conclusions
References
CNN Pre-initialization by Minimalistic Part-Learning for Handwritten Numeral Recognition
1 Introduction
2 Convolutional Neural Network, Pre-initialization and Part-Learning-The Motivation for Our Work
2.1 Convolutional Neural Network (CNN) and Pre-initialization
2.2 Pre-initialization of CNNs
2.3 Learning from Image Parts
3 Proposed CNN Pre-initialization by Minimalistic Part-Learning for Handwritten Numeral Recognition
3.1 Our CNN Architecture
3.2 Proposed Methodology for Minimalistic Part-Learning of Numeral Images
4 Experimental Results
4.1 Experimental Setup
4.2 Results Analysis
5 Conclusions
References
GlosysIC Framework: Transformer for Image Captioning with Sequential Attention
1 Introduction
2 Related Work
3 Methodology
3.1 Encoder
3.2 Decoder
3.3 Transformer
3.4 GlosysIC
4 Experiments
4.1 Datasets
4.2 Implementation Details
4.3 Results
5 Conclusion and Future Work
References
Author Index