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A Joint Embedding Method for Entity Alignment of Knowledge Bases Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Biomedical Event Trigger Detection Based on Hybrid Methods Integrating Word Embeddings

Authors : Lishuang Li, Meiyue Qin, Degen Huang

Published in: Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data

Publisher: Springer Singapore

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Abstract

Trigger detection as the preceding task is of great importance in biomedical event extraction. By now, most of the state-of-the-art systems have been based on single classifiers, and the words encoded by one-hot are unable to represent the semantic information. In this paper, we utilize hybrid methods integrating word embeddings to get higher performance. In hybrid methods, first, multiple single classifiers are constructed based on rich manual features including dependency and syntactic parsed results. Then multiple predicting results are integrated by set operation, voting and stacking method. Hybrid methods can take advantage of the difference among classifiers and make up for their deficiencies and thus improve performance. Word embeddings are learnt from large scale unlabeled texts and integrated as unsupervised features into other rich features based on dependency parse graphs, and thus a lot of semantic information can be represented. Experimental results show our method outperforms the state-of-the-art systems.

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previous chapter Large Scale Semantic Relation Discovery: Toward Establishing the Missing Link Between Wikipedia and Semantic Network
next chapter GRU-RNN Based Question Answering Over Knowledge Base
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Metadata
Title
Biomedical Event Trigger Detection Based on Hybrid Methods Integrating Word Embeddings
Authors
Lishuang Li
Meiyue Qin
Degen Huang
Copyright Year
2016
Publisher
Springer Singapore
Book
Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data

Print ISBN: 978-981-10-3167-0

Electronic ISBN: 978-981-10-3168-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-981-10-3168-7_7

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