TY - GEN
T1 - Information Extraction from Twitter Using DBpedia Ontology
T2 - 1st International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2019
AU - Rosyiq, Ahmad
AU - Hayah, Aina Rahmah
AU - Hidayanto, Achmad Nizar
AU - Naisuty, Meisuchi
AU - Suhanto, Agus
AU - Avuning Budi, Nur Fitriah
PY - 2019/10
Y1 - 2019/10
N2 - As the popular microblogs of social media, Twitter provides a number of short messages of interesting information, like the mention of entities to promote local cultures and tourism places in order for others to know and visit the places. However, the entities mentioned within the tweet may be interpreted differently and vary depending on the context of the tweet. To find the appropriate context of the entities, we need the system that can perform semantic annotation for every entity, especially for the tourism places. In this paper, we provide Named Entity Recognition used to define the candidate entities of the places. Furthermore, by using DBpedia Ontology as a semantic annotation resources we construct the information extraction from the context and semantic of the entities to collect the URI of Wikipedia page of the place. The experiment result showed the system was capable to extract the mentioned place and annotated the URI of Wikipedia with high accuracy which defined by 0.95 of Precision, 0.79 of Recall, and 0.87 of F-Measure.
AB - As the popular microblogs of social media, Twitter provides a number of short messages of interesting information, like the mention of entities to promote local cultures and tourism places in order for others to know and visit the places. However, the entities mentioned within the tweet may be interpreted differently and vary depending on the context of the tweet. To find the appropriate context of the entities, we need the system that can perform semantic annotation for every entity, especially for the tourism places. In this paper, we provide Named Entity Recognition used to define the candidate entities of the places. Furthermore, by using DBpedia Ontology as a semantic annotation resources we construct the information extraction from the context and semantic of the entities to collect the URI of Wikipedia page of the place. The experiment result showed the system was capable to extract the mentioned place and annotated the URI of Wikipedia with high accuracy which defined by 0.95 of Precision, 0.79 of Recall, and 0.87 of F-Measure.
KW - DBpedia
KW - Information Extraction
KW - Named Entity Recognition
KW - Ontology
KW - Twitter
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=85081102660&partnerID=8YFLogxK
U2 - 10.1109/ICIMCIS48181.2019.8985194
DO - 10.1109/ICIMCIS48181.2019.8985194
M3 - Conference contribution
T3 - Proceedings - 1st International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2019
SP - 91
EP - 96
BT - Proceedings - 1st International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 October 2019 through 25 October 2019
ER -