Intro
Preface
Organization
Contents
A Novel Semi-supervised Clustering Algorithm: CoExDBSCAN
1 Introduction
1.1 Motivation
1.2 Background
1.3 Definitions
2 CoExDBSCAN
2.1 Algorithm
2.2 Constraint
3 Cluster Analysis
3.1 Verification
3.2 Evaluation
3.3 Runtime
4 Summary
4.1 Conclusion
4.2 Outlook
References
Amharic Semantic Information Retrieval System
1 Introduction
2 Amharic Language
3 Related Work
3.1 Conventional Information Retrieval
3.2 Semantic Information Retrieval

3.3 Evaluation of Amharic IR Corpora, Resources and NLP Tools
4 Design of Amharic Semantic IR System
4.1 Preprocessing
4.2 Morphological Analysis
4.3 Stopword Removal
4.4 Indexing
4.5 Word Embedding
4.6 Query Expansion
4.7 Matching and Ranking
5 Construction of Amharic IR Resources
5.1 Context-Based Morphologically Annotated Corpora
5.2 Stopword List Construction
6 Experiment
6.1 Implementation
6.2 Experimental Results
6.3 Discussion
7 Conclusion
References
Semantic Similarity Analysis for Entity Set Expansion
1 Introduction

2 Semantic Similarity Analysis: Overview of Methods
2.1 Corpus-Based Methods
2.2 Knowledge-Based Methods
2.3 Analysis of Similarity Metrics
3 Towards Semantic Similarity Analysis for Entity Set Expansion
3.1 Steps in Solving the Entity Set Expansion
3.2 Existing Solutions that Can Be Used for ESE
4 Proposed Solution
4.1 Disambiguation of Senses
4.2 Finding Candidate Entities
4.3 Choosing from Candidates
5 Implementation
5.1 Word Sense Disambiguation
5.2 Finding Candidates
5.3 Evaluating Candidates and Expanding the Seed Set
6 Results and Discussion

6.1 Results
6.2 Discussion
7 Summary
References
Eliciting Semantic Types of Legal Norms in Korean Legislation with Deep Learning
1 Introduction
2 Background
2.1 Problems with Korean Language
2.2 Semantic Types
3 The Legal Taxonomy
3.1 The Basic Concepts
3.2 Semantic Types in Korean Legislations
4 Classification of Legal Norms with Natural Language Processing
4.1 Dataset
4.2 Experiment: Rule-Based Approach
4.3 Experiment: Supervised Machine Learning Approach
5 Related Works
6 Conclusions
References

Context-Aware Knowledge Management as an Enabler for Human-Machine Collective Intelligence
1 Introduction
2 Modern Trends in CAKM for SCPS
2.1 Role-Based Organization
2.2 Dynamic Motivation Mechanisms
2.3 Multi-aspect Ontology
3 CAKM Implementation
3.1 Role-Based Organization
3.2 Dynamic Motivation
3.3 Multi-aspect Ontology
4 Human-Machine Collective Intelligence
4.1 Modes of Human-AI Collaboration
4.2 Concept of Human-Machine Collective Intelligence Environment
4.3 Implementation of the Human-AI Collaboration Modes
5 Conclusions
References