Olelo: A Question Answering Application for Biomedicine

Neves, Mariana; Folkerts, Hendrik; Jankrift, Marcel; Niedermeier, Julian; Stachewicz, Toni; Tietböhl, Sören; Kraus, Milena; Uflacker, Matthias

doi:10.18653/v1/p17-4011

Cited by 2 publications

(2 citation statements)

References 9 publications

(7 reference statements)

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“…So, ontology and predicate-argument structures (PAS) make extracting answers easier. The resulting answer goes through a process where the system ranks the document so that the query will match the keywords obtained [7][8][9] [10].…”

Section: Introductionmentioning

confidence: 99%

Question Answering using Ontology for Sumedang Larang History with Support Vector Machine Based on Telegram Bot

Perangin-Angin

Baizal²,

Richasdy³

2022

mib

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Technological developments affect many aspects, one of which is historical education. History lessons can shape students' personalities and encourage an interest in historical knowledge. There are many stories from Indonesian history, one of which is the Sumedang Larang Kingdom. The Sumedang Larang Kingdom is one of the Islamic kingdoms in Pasundan. However, not many people know about this kingdom. The millennial generation is technologically advanced, so they can take advantage of technological advances to quickly introduce the history of Sumedang Larang. One of them utilizes the telegram bot using the Application Programming Interface (API), which can connect the system to the telegram platform. In addition, this technology can be used as a history learning attraction using the question answering system (QA). Our research aims to build a QA system that can introduce the history of Sumedang Larang to the millennial generation. Because this system uses ontology knowledge with concepts related to the Sumedang Larang domain, it can focus on the history of Sumedang Larang. Applying the support vector machine (SVM) algorithm to process classification text can make it easier to search for text categories. The test results show the performance of the SVM method with a test size parameter of 0.5, such as 74% and 78%. The performance test results are accuracy scores in the subject category and object classification.

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Section: Introductionmentioning

confidence: 99%

Question Answering using Ontology for Sumedang Larang History with Support Vector Machine Based on Telegram Bot

Perangin-Angin

Baizal²,

Richasdy³

2022

mib

View full text Add to dashboard Cite

show abstract

“…The advantage of using an ontology is its ability to analyze questions in natural language so that the system can give the correct answer [10]. QAS has been applied in various fields such as the biomedical field [11]. This QAS named Olelo accepts questions that ask for answers in the form of factoids (short answers), definitions (explanations of a concept), and summaries (short stories/conclusions of a topic).…”

Section: Introductionmentioning

confidence: 99%

Question Answering System Using Semantic Reasoning on Ontology for The History of The Sumedang Larang Kingdom

Anggrayni¹,

Baizal²,

Richasdy³

2022

bits

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Studying history can train us to understand the sequence of events and increase a sense of nationalism in the younger generation. However, today's young generation views studying history as boring and unimportant. Studying history is considered boring because it has the stereotype of having to learn by reading long writings in books. Therefore, in this study, a Question Answering System (QAS) was built using an ontology to get historical information and get to know the culture. With QAS, users don't have to read long sentences and spend a lot of time searching for historical information, users can also ask questions in natural language without having to pay attention to sentence structure. The ontology was chosen to be able to build a knowledge base on the historical domain and SPARQL was used to find answers in the ontology. The construction of this system is expected not only to help introduce the history of the Sumedang Larang Kingdom but also to be able to introduce the attraction of cultural tourism in Indonesia, especially the Sumedang Larang Kingdom. The results of the evaluation with the system accuracy test showed a result of 87%.

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Olelo: A Question Answering Application for Biomedicine

Cited by 2 publications

References 9 publications

Question Answering using Ontology for Sumedang Larang History with Support Vector Machine Based on Telegram Bot

Question Answering using Ontology for Sumedang Larang History with Support Vector Machine Based on Telegram Bot

Question Answering System Using Semantic Reasoning on Ontology for The History of The Sumedang Larang Kingdom

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