title: A Novel Sample Selection Strategy for Imbalanced Data of Biomedical Event Extraction with Joint Scoring Mechanism.
abstract: Biomedical event extraction is an important and difficult task in bioinformatics. With the rapid growth of biomedical literature, the extraction of complex events from unstructured text has attracted more attention. However, the annotated biomedical corpus is highly imbalanced, which affects the performance of the classification algorithms. In this study, a sample selection algorithm based on sequential pattern is proposed to filter negative samples in the training phase. Considering the joint information between the trigger and argument of multiargument events, we extract triplets of multiargument events directly using a support vector machine classifier. A joint scoring mechanism, which is based on sentence similarity and importance of trigger in the training data, is used to correct the predicted results. Experimental results indicate that the proposed method can extract events efficiently.
authors.affiliation: College of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China; Library, Inner Mongolia University for Nationalities, Tongliao, Inner Mongolia 028000, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Lu
authors.affiliation: College of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China; Library, Inner Mongolia University for Nationalities, Tongliao, Inner Mongolia 028000, China.
authors.forename: Xiaolei
authors.initials: X
authors.lastname: Ma
authors.affiliation: College of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China.
authors.forename: Yinan
authors.identifier: 0000-0001-5786-9178
authors.initials: Y
authors.lastname: Lu
authors.affiliation: College of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China.
authors.forename: Yuxin
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: College of Computer Science and Technology, Inner Mongolia University for Nationalities, Tongliao, Inner Mongolia 028000, China.
authors.forename: Zhili
authors.initials: Z
authors.lastname: Pei
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D004194:Disease; D005786:Gene Expression Regulation; D006801:Humans; D015233:Models, Statistical; D009323:Natural Language Processing; D009369:Neoplasms / Q000000981:diagnostic imaging; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D060388:Support Vector Machine