Semantic Event Extraction from Biological Texts Using a Kernel-Based Method

Faiz, Rim; Amami, Maha; Elkhlifi, Aymen

doi:10.1007/978-3-319-02999-3_5

Cited by 3 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[ 47 ] discuss comprehensive surveys of methods for the extraction of network information from the scientific literature and the evaluation of extraction methods against reference corpora. Semantic-based approaches such as [ 48 ] will make their mark in the coming years. Event extraction is similar to association extraction but instead of separately extracting various relations between different entities in text, this task focuses on identifying specific events and the various players involved in it (arguments).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

González¹,

et al. 2015

View full text Add to dashboard Cite

Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

González¹,

et al. 2015

View full text Add to dashboard Cite

show abstract

“…While entity recognition has been exploited as a powerful approach towards automatic NER retrieval, there has recently been an increased interest to find more complex structural information and more abundant knowledge in documents [ 9 ]. Hence, as a more recent development, moving beyond the purpose of entity recognition, the GENIA task in the BioNLP 2009/2011 shared tasks [ 10 , 11 ] was set to identify and extract nine biomedical events from GENIA-based corpus texts [ 12 ], including gene expression, transcription, protein catabolism, localization, binding, phosphorylation, regulation, positive regulation, and negative regulation.…”

Section: Introductionmentioning

confidence: 99%

A Novel Feature Selection Strategy for Enhanced Biomedical Event Extraction Using the Turku System

Xia

Fang

Zhang

2014

BioMed Research International

View full text Add to dashboard Cite

Feature selection is of paramount importance for text-mining classifiers with high-dimensional features. The Turku Event Extraction System (TEES) is the best performing tool in the GENIA BioNLP 2009/2011 shared tasks, which relies heavily on high-dimensional features. This paper describes research which, based on an implementation of an accumulated effect evaluation (AEE) algorithm applying the greedy search strategy, analyses the contribution of every single feature class in TEES with a view to identify important features and modify the feature set accordingly. With an updated feature set, a new system is acquired with enhanced performance which achieves an increased F-score of 53.27% up from 51.21% for Task 1 under strict evaluation criteria and 57.24% according to the approximate span and recursive criterion.

show abstract

Methods for Rational Design and Discovery of Multitarget Drugs

Wang

Yang²

2022

Polypharmacology

View full text Add to dashboard Cite

Semantic Event Extraction from Biological Texts Using a Kernel-Based Method

Cited by 3 publications

References 15 publications

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

A Novel Feature Selection Strategy for Enhanced Biomedical Event Extraction Using the Turku System

Methods for Rational Design and Discovery of Multitarget Drugs

Contact Info

Product

Resources

About