@article{ART002391657},
author={Song min-sun},
title={Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles},
journal={Journal of the Korean Society for Information Management},
issn={1013-0799},
year={2018},
volume={35},
number={3},
pages={101-121},
doi={10.3743/KOSIM.2018.35.3.101}
TY - JOUR
AU - Song min-sun
TI - Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles
JO - Journal of the Korean Society for Information Management
PY - 2018
VL - 35
IS - 3
PB - 한국정보관리학회
SP - 101
EP - 121
SN - 1013-0799
AB - This study proposes the analysis method in sentence semantics that can be automatically identified and processed as appropriate items in the system according to the composition of the sentences contained in the data corresponding to the logical semantic structure metadata of the research papers. In order to achieve the purpose, the structure of sentences corresponding to ‘Research Objectives’ and ‘Research Outcomes’ among the semantic structure metadata was analyzed based on the number of words, the link word types, the role of many-appeared words in sentences, and the end types of a word. As a result of this study, the number of words in the sentences was 38 in ‘Research Objectives’ and 212 in ‘Research Outcomes’. The link word types in ‘Research Objectives’ were occurred in the order such as Causality, Sequence, Equivalence, In-other-word/Summary relation, and the link word types in ‘Research Outcomes’ were appeared in the order such as Causality, Equivalence, Sequence, In-other-word/Summary relation. Analysis target words like ‘역할(Role)’, ‘요인(Factor)’ and ‘관계(Relation)’ played a similar role in both purpose and result part, but the role of ‘연구(Study)’ was little different. Finally, the verb endings in sentences were appeared many times such as ‘∼고자’, ‘∼였다’ in ‘Research Objectives’, and ‘∼었다’, ‘∼있다’, ‘∼였다’ in ‘Research Outcomes’. This study is significant as a fundamental research that can be utilized to automatically identify and input the metadata element reflecting the common logical semantics of research papers in order to support researchers’ scholarly sensemaking.
KW - scholarly sensemaking;logical semantic structure;research articles;metadata;analyzing the sentence structure;sentence semantics
DO - 10.3743/KOSIM.2018.35.3.101
ER -
Song min-sun. (2018). Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles. Journal of the Korean Society for Information Management, 35(3), 101-121.
Song min-sun. 2018, "Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles", Journal of the Korean Society for Information Management, vol.35, no.3 pp.101-121. Available from: doi:10.3743/KOSIM.2018.35.3.101
Song min-sun "Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles" Journal of the Korean Society for Information Management 35.3 pp.101-121 (2018) : 101.
Song min-sun. Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles. 2018; 35(3), 101-121. Available from: doi:10.3743/KOSIM.2018.35.3.101
Song min-sun. "Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles" Journal of the Korean Society for Information Management 35, no.3 (2018) : 101-121.doi: 10.3743/KOSIM.2018.35.3.101
Song min-sun. Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles. Journal of the Korean Society for Information Management, 35(3), 101-121. doi: 10.3743/KOSIM.2018.35.3.101
Song min-sun. Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles. Journal of the Korean Society for Information Management. 2018; 35(3) 101-121. doi: 10.3743/KOSIM.2018.35.3.101
Song min-sun. Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles. 2018; 35(3), 101-121. Available from: doi:10.3743/KOSIM.2018.35.3.101
Song min-sun. "Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles" Journal of the Korean Society for Information Management 35, no.3 (2018) : 101-121.doi: 10.3743/KOSIM.2018.35.3.101
