Knowledge Discovery from Multi-Sourced Data

Chapter 1 Introduction

1.1 Knowledge Discovery

1.2 Main Challenges

1.3 Book Overview

Chapter 2 Functional-dependency-based truth discovery for isomorphic data

2.1 Handling independent constraints

2.2 Handling inter-related constraints

2.3 Inter-source data aggregation

2.4 Update source weights

Chapter 3 Denial-constraint-based truth discovery for isomorphic data

Describe the truth discovery strategies for isomorphic data based on denial constraints

4.1 Denial constraint transformation

4.2 Optimized solution

4.3 Scalable strategies

Chapter 4 Pattern discovery for heterogeneous data

4.1 Problem definition for multi-source heterogeneous data

4.2 Optimization framework

4.3 PatternFinder algorithm

4.4 The optimized grouping strategy

Chapter 5 Deep fact discovery for text data

5.1 Fact extraction via mining patterns

5.2 The CNN-LSTM architecture

5.3 The fact encoder and pattern embedding

5.4 Training and inference