@article{,
    author = {Kim, Yeongsu; Lee, Seungwoo; Dollmann, Markus; Geierhos, Michaela},
    title = {Improving Classifiers for Semantic Annotation of Software Requirements with Elaborate Syntactic Structure},
    editor = {},
    booktitle = {},
    series = {},
    journal = {International Journal of Advanced Science and Technology},
    address = {},
    publisher = {SERSC Australia},
    edition = {},
    year = {2018},
    isbn = {},
    volume = {112},
    number =  {},
    pages = {123-136},
    url = {},
    doi = {10.14257/ijast.2018.112.12},
    keywords = {Software Engineering ; Natural Language Processing ; Semantic Annotation ; Machine Learning ; Feature Engineering ; Syntactic Structure},
    abstract = {A user generally writes software requirements in ambiguous and incomplete form by using natural language; therefore, a software developer may have difficulty in clearly understanding what the meanings are. To solve this problem with automation, we propose a classifier for semantic annotation with manually pre-defined semantic categories. To improve our classifier, we carefully designed syntactic features extracted by constituency and dependency parsers. Even with a small dataset and a large number of classes, our proposed classifier records an accuracy of 0.75, which outperforms the previous model, REaCT.},
    note = {},
    
    
    
}