Implementation of Named Entity Recognition with a Developing Question Answering System: A Case Study in the Merapi Volcano Museum

Arfiani Nur Khusna(1*), Okhy Kharisma Putri(2), Dimas Chaerul Ekty Saputra(3)


(1) Universitas Ahmad Dahlan
(2) Universitas Ahmad Dahlan
(3) Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Merapi volcano museum is a place to get some information about active mountain activities, the general public can access the website page at mgm.slemankab.go.id. Indeed, visitors are given easy access, but the information provided by the website is not fully complete, causing visitors to feel dissatisfied. Based on the results of a questionnaire from 40 respondents, it was found that 50.55% of website visitors did not get the information they wanted. Therefore, in this research, we built a Question Answering System (QAS) using the Named Entity Recognition (NER) method that has been implemented into Telegram. To improve the performance of the QAS system, testing and analysis has been carried out with a "white box" approach. The results show that the QAS system has 3 regions and 3 independent paths, with path 1 being 1-2-3-4-11, path 2 being 1-2-3-4-5-6-7-8-11, and path 3 being 1-2-3-4-5-6-7-9-10-11. Based on the results of this study, all three paths can produce the correct answer.

Keywords


Named Entity Recognitionl; Question Answering System; Museum; White-Box Testing; Dissatisfied Information

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References


Azmi, N. S. A., Singkaravanit-Ogawa, S., Ikeda, K., Kitakura, S., Inoue, Y., Narusaka, Y., Shirasu, K., Kaido, M., Mise, K., & Takano, Y. (2018). Inappropriate expression of an NLP effector in Colletotrichum orbiculare impairs infection on cucurbitaceae cultivars via plant recognition of the C-terminal region. Molecular Plant-Microbe Interactions, 31(1), 101–111. https://doi.org/10.1094/MPMI-04-17-0085-FI

Bougar, M., & Ziyati, E. H. (2019). Stemming algorithm for arabic text using a parallel data processing. Advances in Intelligent Systems and Computing, 797(July), 261–268. https://doi.org/10.1007/978-981-13-1165-9_23

Brown, K., & Mairesse, F. (2018). The definition of the museum through its social role. Curator: The Museum Journal, 61(4), 525–539. https://doi.org/10.1111/cura.12276

Garousi, V., Bauer, S., & Felderer, M. (2020). NLP-assisted software testing: A systematic mapping of the literature. Information and Software Technology, 126, 1–29. https://doi.org/10.1016/j.infsof.2020.106321

Gusmita, R. H., Durachman, Y., Harun, S., Firmansyah, A. F., Sukmana, H. T., & Suhaimi, A. (2014). A rule-based question answering system on relevant documents of Indonesian Quran Translation. 2014 International Conference on Cyber and IT Service Management, CITSM 2014, 104–107. https://doi.org/10.1109/CITSM.2014.7042185

Khusna, A. N., & Agustina, I. (2018). Implementation of Information Retrieval Using TF-IDF Weighting Method On Detik.Com’s Website. TSSA-IEEE.

Ladani, D. J., & Desai, N. P. (2020). Stopword Identification and Removal Techniques on TC and IR applications: A Survey. 2020 6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020, 466–472. https://doi.org/10.1109/ICACCS48705.2020.9074166

Luan, Y., Wadden, D., He, L., Shah, A., Ostendorf, M., & Hajishirzi, H. (2019). A general framework for information extraction using dynamic span graphs. NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference, 1, 3036–3046. https://doi.org/10.18653/v1/n19-1308

Pramanik, S., & Hussain, A. (2019). Text normalization using memory augmented neural networks. Speech Communication, 109, 15–23. https://doi.org/10.1016/j.specom.2019.02.003

Prasad, G. N. R. (2021). Identification of Bloom ’ s Taxonomy level for the given Question paper using NLP Tokenization technique Turkish Journal of Computer and Mathematics Education Research Article Identification of Cognitive level of Question. Turkish Journal of Computer and Mathematics Education, 12(13), 1872–1875.

Project, M. D. (2019). N-Grams as a Measure of Naturalness and Complexity. Department of computer science and media technology (CM), Digitala Vetenskapliga Arkivet.

Qiu, M., Housh, M., & Ostfeld, A. (2020). A two-stage LP-NLP methodology for the least-cost design and operation of water distribution systems. Water (Switzerland), 12(5), 1–21. https://doi.org/10.3390/W12051364

Ramos-Merino, M., Álvarez-Sabucedo, L. M., Santos-Gago, J. M., & Sanz-Valero, J. (2018). A BPMN Based Notation for the Representation of Workflows in Hospital Protocols. Journal of Medical Systems, 42(10). https://doi.org/10.1007/s10916-018-1034-2

Sapitri, A. I., & Al-faraby, S. (2018). Analisis Metode Pattern Based Approach Question Answering System Pada Dataset Hukum Islam Berbasis Bahasa Indonesia. Media Informatika Budidarma (MIB), 2(4), 159–164. http://dx.doi.org/10.30865/mib.v2i4.950

Syaikhuddin, M. M., Anam, C., Rinaldi, A. R., & Conoras, M. E. B. (2018). Conventional Software Testing Using White Box Method. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 3(1), 65–72. https://doi.org/10.22219/kinetik.v3i1.231

Wick, C., & Puppe, F. (2018). Fully Convolutional Neural Networks for Page Segmentation of Historical Document Images of Historical Document Images. In 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), 287–292. https://doi.org/10.1109/DAS.2018.39

Yadav, V., & Bethard, S. (2019). A survey on recent advances in named entity recognition from deep learning models. ArXiv Preprint ArXiv:1910.11470. https://doi.org/10.48550/arXiv.1910.11470

Yu, W., Wu, L., Deng, Y., Mahindru, R., Zeng, Q., Guven, S., & Jiang, M. (2020). A Technical Question Answering System with Transfer Learning. 92–99. https://doi.org/10.18653/v1/2020.emnlp-demos.13

Zhang, N., Chen, X., Xie, X., Deng, S., Tan, C., Chen, M., Huang, F., Si, L., & Chen, H. (2021). Document-level Relation Extraction as Semantic Segmentation. 3999–4006. https://doi.org/10.24963/ijcai.2021/551


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DOI: https://doi.org/10.26714/jichi.v3i1.9205

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Journal of Intelligent Computing and Health Informatics (JICHI)
ISSN 2715-6923 (print) | 2721-9186 (online)
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Department of Informatics
Faculty of Engineering
Universitas Muhammadiyah Semarang

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