Information Extraction from Twitter Using DBpedia Ontology: Indonesia Tourism Places

被引:0
|
作者
Rosyiq, Ahmad [1 ]
Hayah, Aina Rahmah [1 ]
Hidayanto, Achmad Nizar [1 ]
Naisuty, Meisuchi [1 ]
Suhanto, Agus [1 ]
Budi, Nur Fitriah Avuning [1 ]
机构
[1] Univ Indonesia, Fac Comp Sci, Jakarta, Indonesia
来源
2019 INTERNATIONAL CONFERENCE ON INFORMATICS, MULTIMEDIA, CYBER AND INFORMATION SYSTEM (ICIMCIS) | 2019年
关键词
Information Extraction; Named Entity Recognition; Ontology; DBpedia; Wikipedia; Twitter;
D O I
10.1109/icimcis48181.2019.8985194
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:91 / 96
页数:6
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