Penerapan Bidirectional Long Short-Term Memory dalam Sistem Tanya Jawab Fakultas Ilmu Komputer Universitas Brawijaya
Kata Kunci:
chatbot, text preprocessing, generative model, LSTM, Seq2SeqAbstrak
Naskah ini akan diterbitkan di Konferensi Internasional EECCIS
Referensi
Anki, P., Bustamam, A., Al-Ash, H.S., Sarwinda, D., 2021. Intelligent Chatbot Adapted from Question and Answer System Using RNN-LSTM Model. J. Phys.: Conf. Ser. 1844, 012001. https://doi.org/10.1088/1742-6596/1844/1/012001
Bachtiar, F.A., Dysham, A.A., Fauzulhaq, A.D., Azzam, J.S., Aryadita, H., 2023. FLUENT: Factoid Retrieval Based Chatbot Using LSTM, in: 2023 1st International Conference on Advanced Engineering and Technologies (ICONNIC). Presented at the 2023 1st International Conference on Advanced Engineering and Technologies (ICONNIC), pp. 153–158. https://doi.org/10.1109/ICONNIC59854.2023.10467226
Bahdanau, D., Cho, K., Bengio, Y., 2016. Neural Machine Translation by Jointly Learning to Align and Translate.
Chandra, Y.W., Suyanto, S., 2019. Indonesian Chatbot of University Admission Using a Question Answering System Based on Sequence-to-Sequence Model. Procedia Computer Science 157, 367–374. https://doi.org/10.1016/j.procs.2019.08.179
Dhyani, M., Kumar, R., 2021. An intelligent Chatbot using deep learning with Bidirectional RNN and attention model. Materials Today: Proceedings 34, 817–824. https://doi.org/10.1016/j.matpr.2020.05.450
Hosameldeen, O., Abousamra, R., Al-Aqrabi, H., Embarak, O., Durrani, U., 2023. Improving the Accuracy of Customer Service Seq2Seq Chatbots Through Dataset Pruning. https://doi.org/10.20944/preprints202303.0070.v1
Khadija, M.A., Nurharjadmo, W., Widyawan, 2022. Deep Learning Generative Indonesian Response Model Chatbot for JKN-KIS, in: 2022 1st International Conference on Smart Technology, Applied Informatics, and Engineering (APICS). Presented at the 2022 International Conference on Smart Technology, Applied Informatics, and Engineering (APICS), IEEE, Surakarta, Indonesia, pp. 70–74. https://doi.org/10.1109/APICS56469.2022.9918686
Setiawan, B.A., Utami, E., Hartanto, A.D., 2021. Banjarese Chatbot Using Seq2Seq Model, in: 2021 4th International Conference on Information and Communications Technology (ICOIACT). Presented at the 2021 4th International Conference on Information and Communications Technology (ICOIACT), IEEE, Yogyakarta, Indonesia, pp. 233–238. https://doi.org/10.1109/ICOIACT53268.2021.9563915
Sojasingarayar, A., 2020. Seq2Seq AI Chatbot with Attention Mechanism. Artificial Intelligence.
Thorat, S.A., Jadhav, V., 2020. A Review on Implementation Issues of Rule-based Chatbot Systems. SSRN Journal. https://doi.org/10.2139/ssrn.3567047
Zuraiyah, T.A., Utami, D.K., Herlambang, D., 2019. IMPLEMENTASI CHATBOT PADA PENDAFTARAN MAHASISWA BARU MENGGUNAKAN RECURRENT NEURAL NETWORK. tekno 24, 91–101. https://doi.org/10.35760/tr.2019.v24i2.2388
Anki, P., Bustamam, A., Al-Ash, H.S., Sarwinda, D., 2021. Intelligent Chatbot Adapted from Question and Answer System Using RNN-LSTM Model. J. Phys.: Conf. Ser. 1844, 012001. https://doi.org/10.1088/1742-6596/1844/1/012001
Bachtiar, F.A., Dysham, A.A., Fauzulhaq, A.D., Azzam, J.S., Aryadita, H., 2023. FLUENT: Factoid Retrieval Based Chatbot Using LSTM, in: 2023 1st International Conference on Advanced Engineering and Technologies (ICONNIC). Presented at the 2023 1st International Conference on Advanced Engineering and Technologies (ICONNIC), pp. 153–158. https://doi.org/10.1109/ICONNIC59854.2023.10467226
Bahdanau, D., Cho, K., Bengio, Y., 2016. Neural Machine Translation by Jointly Learning to Align and Translate.
Chandra, Y.W., Suyanto, S., 2019. Indonesian Chatbot of University Admission Using a Question Answering System Based on Sequence-to-Sequence Model. Procedia Computer Science 157, 367–374. https://doi.org/10.1016/j.procs.2019.08.179
Dhyani, M., Kumar, R., 2021. An intelligent Chatbot using deep learning with Bidirectional RNN and attention model. Materials Today: Proceedings 34, 817–824. https://doi.org/10.1016/j.matpr.2020.05.450
Hosameldeen, O., Abousamra, R., Al-Aqrabi, H., Embarak, O., Durrani, U., 2023. Improving the Accuracy of Customer Service Seq2Seq Chatbots Through Dataset Pruning. https://doi.org/10.20944/preprints202303.0070.v1
Khadija, M.A., Nurharjadmo, W., Widyawan, 2022. Deep Learning Generative Indonesian Response Model Chatbot for JKN-KIS, in: 2022 1st International Conference on Smart Technology, Applied Informatics, and Engineering (APICS). Presented at the 2022 International Conference on Smart Technology, Applied Informatics, and Engineering (APICS), IEEE, Surakarta, Indonesia, pp. 70–74. https://doi.org/10.1109/APICS56469.2022.9918686
Setiawan, B.A., Utami, E., Hartanto, A.D., 2021. Banjarese Chatbot Using Seq2Seq Model, in: 2021 4th International Conference on Information and Communications Technology (ICOIACT). Presented at the 2021 4th International Conference on Information and Communications Technology (ICOIACT), IEEE, Yogyakarta, Indonesia, pp. 233–238. https://doi.org/10.1109/ICOIACT53268.2021.9563915
Sojasingarayar, A., 2020. Seq2Seq AI Chatbot with Attention Mechanism. Artificial Intelligence.
Thorat, S.A., Jadhav, V., 2020. A Review on Implementation Issues of Rule-based Chatbot Systems. SSRN Journal. https://doi.org/10.2139/ssrn.3567047
Zuraiyah, T.A., Utami, D.K., Herlambang, D., 2019. IMPLEMENTASI CHATBOT PADA PENDAFTARAN MAHASISWA BARU MENGGUNAKAN RECURRENT NEURAL NETWORK. tekno 24, 91–101. https://doi.org/10.35760/tr.2019.v24i2.2388
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