Natural language processing and information extraction

Abstract

This thesis presents original research in the subject of Machine Learning and more specifically in the fields of Natural Language Processing and Information Extraction. We focus on the following research problems which concern specific tasks in Natural Language Processing and Information Extraction: a) improving clinical decision making through Biomedical Entity Recognition, b) advancing Biomedical Argumentation Mining, c) efficient Language Modeling with distant contextual information and d) deploying Natural Language Processing applications in the real world. First, we present a series of novel architectures for refined Biomedical Entity Recognition, with specific focus in Evidence-Based Medicine entities. These semantically rich entities, which are more descriptive than generic biomedical entity types, offer useful insights in the treatment formulation process and are harder for Machine Learning models to identify. The incrementally proposed changes to the Deep Neural Network archi ...
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DOI
10.12681/eadd/50236
Handle URL
http://hdl.handle.net/10442/hedi/50236
ND
50236
Alternative title
Επεξεργασία φυσικής γλώσσας και εξαγωγή πληροφοριών από κείμενα
Author
Stylianou, Nikolaos (Father's name: Evangelos)
Date
2021
Degree Grantor
Aristotle University Of Thessaloniki (AUTH)
Committee members
Βλαχάβας Ιωάννης
Βακάλη Αθηνά
Τσουμάκας Γρηγόριος
Βασιλειάδης Νικόλαος
Τέφας Αναστάσιος
Κουμπαράκης Μανόλης
Αλετράς Νικόλαος
Discipline
Natural SciencesComputer and Information Sciences ➨ Artificial Intelligence
Keywords
Natural language processing; Information extraction; Machine learning; Deep learning
Country
Greece
Language
English
Description
im., tbls., fig., ch.
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