Mining Structures of Factual Knowledge from Text : An Effort-Light Approach /
The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mini...
| Main Authors: | , |
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| Corporate Author: | |
| Format: | Book |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2018
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| Edition: | 1st ed. 2018 |
| Series: | Synthesis Lectures on Data Mining and Knowledge Discovery,
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| Subjects: |
Table of Contents:
- Acknowledgments
- Introduction
- Background
- Literature Review
- Entity Recognition and Typing with Knowledge Bases
- Fine-Grained Entity Typing with Knowledge Bases
- Synonym Discovery from Large Corpus
- Joint Extraction of Typed Entities and Relationships
- Pattern-Enhanced Embedding Learning for Relation Extraction
- Heterogeneous Supervision for Relation Extraction
- Indirect Supervision: Leveraging Knowledge from Auxiliary Tasks
- Mining Entity Attribute Values with Meta Patterns
- Open Information Extraction with Global Structure Cohesiveness
- Open Information Extraction with Global Structure Cohesiveness
- Applications
- Conclusions
- Vision and Future Work
- Bibliography
- Authors' Biographies