TY - GEN
T1 - Ontology of academic sentence dependencies for a verb choice suggestion
AU - Kanjanawattana, Sarunya
AU - Kimura, Masaomi
PY - 2018/9
Y1 - 2018/9
N2 - Non-native researchers encountered a problem of lacking academic writing skill. During the writing, we may accidentally use a word repeatedly due to our familiarity that reduces a quality of writing. To solve the problem, a paraphrase is a good option. It helps the manuscript read more flowery by reducing duplicate words and refining sentence alignments. In this study, we propose a novel idea to use a sentence dependency ontology to suggest possible verbs replaceable on existing context without influence to the original intention. We created an ontology-based system and designed a new ontology. To discover a list of verb choices, our idea is based on sentence dependency, especially a dependency between subject and verb (nsubj) as well as a relationship between verb and object (dobj). We chose them because these two dependencies had a strong relationship to the verb of the sentence. To evaluate the system, we compared the efficiencies of two different systems, i.e., a tradition system utilizing synonyms as word choices and our ontology-based system. As the results, ours provided the better performance rather than the traditional system. This clarifies that our system should be a proper solution for studies on paraphrasing.
AB - Non-native researchers encountered a problem of lacking academic writing skill. During the writing, we may accidentally use a word repeatedly due to our familiarity that reduces a quality of writing. To solve the problem, a paraphrase is a good option. It helps the manuscript read more flowery by reducing duplicate words and refining sentence alignments. In this study, we propose a novel idea to use a sentence dependency ontology to suggest possible verbs replaceable on existing context without influence to the original intention. We created an ontology-based system and designed a new ontology. To discover a list of verb choices, our idea is based on sentence dependency, especially a dependency between subject and verb (nsubj) as well as a relationship between verb and object (dobj). We chose them because these two dependencies had a strong relationship to the verb of the sentence. To evaluate the system, we compared the efficiencies of two different systems, i.e., a tradition system utilizing synonyms as word choices and our ontology-based system. As the results, ours provided the better performance rather than the traditional system. This clarifies that our system should be a proper solution for studies on paraphrasing.
KW - Natural language processing
KW - Ontology
KW - Paraphrase
KW - Sentence dependency
KW - Word choices suggestion
UR - http://www.scopus.com/inward/record.url?scp=85073497724&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073497724&partnerID=8YFLogxK
U2 - 10.1109/ICDIM.2018.8847019
DO - 10.1109/ICDIM.2018.8847019
M3 - Conference contribution
AN - SCOPUS:85073497724
T3 - 2018 13th International Conference on Digital Information Management, ICDIM 2018
SP - 39
EP - 44
BT - 2018 13th International Conference on Digital Information Management, ICDIM 2018
A2 - Ariwa, Ezendu
A2 - Pichappan, Pit
A2 - Pichappan, Pit
A2 - El-Medany, Wael M
A2 - Naeem, Asif
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Conference on Digital Information Management, ICDIM 2018
Y2 - 24 September 2018 through 26 September 2018
ER -