Lemmatization and normalization

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Table of contents

List of Figures
List of Tables
Abstract
Introduction
1 Problem Statement
1.1 Background of the Problem
1.2 Purpose and Significance of the Study
2 Research Questions
3 Thesis Contributions
3.1 Research Design and Limitations
4 Thesis Outline
1 Background & Related Work
1.1 Introduction
1.2 Biological Background
1.2.1 Why the seed development of Arabidopsis thaliana?
1.2.2 A. thaliana regulatory network basics
1.3 The seed development network in A. Thaliana
1.4 Knowledge Extraction
1.4.1 Knowledge models, domains and IE
1.4.2 Knowledge Extraction for Biology and A.Thaliana
1.5 Knowledge Expressed in Text: the Corpus
1.5.1 The building blocks: entities and semantic relations
1.5.2 Corpus
1.6 Information Extraction
1.6.1 Defining IE
1.6.2 Evaluating IE systems
1.6.3 IE Systems
1.7 The Alvis ecosystem
1.8 Conclusion
2 Data
2.1 Introduction
2.1.1 Tasks & Development Phases
2.1.2 People
2.2 Tools
2.2.1 Collaborative Tools
2.2.2 Documentation
2.2.3 Annotation
2.3 Model
2.3.1 Conceptual Model
2.3.2 Annotation Model
2.3.3 Model Transformations
2.4 Corpus
2.4.1 Source
2.4.2 Corpus Annotation
2.5 Results and Discussion
2.6 Conclusion
3 Relation Extraction
3.1 Introduction
3.1.1 Information Extraction
3.2 Linguistic Pre-processing
3.2.1 Tokenization and segmentation
3.2.2 Lemmatization and normalization
3.2.3 Syntactic Parsing
3.3 Representation
3.3.1 Introduction
3.3.2 From text files to complex sentence objects
3.3.3 From sentences to candidate relations
3.3.4 From candidate relations to paths
3.3.5 From paths to a machine-learning ready representation
3.4 Classification
3.4.1 Introduction
3.4.2 Support Vector Machines
3.5 Adding Semantic Information
3.5.1 Introduction
3.5.2 Manual Classes
3.5.3 WordNet
3.5.4 Textual similarity
3.5.5 Distributional Semantics
3.6 Results
3.6.1 Experimental setup
3.6.2 Experimental validation
3.7 Discussion
3.8 Conclusion
4 Relation Extraction on A. thaliana
4.1 Introduction
4.2 SeeDev in BioNLP-ST ’16
4.3 AlvisRE on Arabidopsis thaliana
4.3.1 Optimizing the SVM margin parameter
4.3.2 Exploring different relation types
4.3.3 The impact of model transformations on Relation Extraction
4.3.4 AlvisRE compared to the SeeDev participants
4.4 Discussion
Conclusion & Future Work
1 Conclusion
2 Future Work
2.1 Data
2.2 Information Extraction
Appendices
A Manual Classes for LLL
B Trigger words for Bacteria Biotopes
C A complete AlvisRE input file
D The list of the articles in the Arabidopsis Thaliana corpus.
E The Arabidopsis Thaliana Seed Development conceptual model in detail.
F The Arabidopsis Thaliana Seed Development annotation model in detail.
Bibliography