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Journal : International Journal of Advances in Intelligent Informatics

Academic expert finding using BERT pre-trained language model Mannix, Ilma Alpha; Yulianti, Evi
International Journal of Advances in Intelligent Informatics Vol 10, No 2 (2024): May 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v10i2.1497

Abstract

Academic expert finding has numerous advantages, such as: finding paper-reviewers, research collaboration, enhancing knowledge transfer, etc. Especially, for research collaboration, researchers tend to seek collaborators who share similar backgrounds or with the same native languages. Despite its importance, academic expert findings remain relatively unexplored within the context of Indonesian language. Recent studies have primarily relied on static word embedding techniques such as Word2Vec to match documents with relevant expertise areas. However, Word2Vec is unable to capture the varying meanings of words in different contexts. To address this research gap, this study employs Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art contextual embedding model. This paper aims to examine the effectiveness of BERT on the task of academic expert finding. The proposed model in this research consists of three variations of BERT, namely IndoBERT (Indonesian BERT), mBERT (Multilingual BERT), and SciBERT (Scientific BERT), which will be compared to a static embedding model using Word2Vec. Two approaches were employed to rank experts using the BERT variations: feature-based and fine-tuning. We found that the IndoBERT model outperforms the baseline by 6–9% when utilizing the feature-based approach and shows an improvement of 10–18% with the fine-tuning approach. Our results proved that the fine-tuning approach performs better than the feature-based approach, with an improvement of 1–5%.  It concludes by using IndoBERT, this research has shown an improved effectiveness in the academic expert finding within the context of Indonesian language.
Co-Authors Abdul Haris Abdurrohman, Jafar Abro, Fikri Adriana, Risda Agung Bambang Setio Utomo Agus Sugandha Ahmad Dahlan Alfina, Ika Alie, M. Fadhiel Aminuddin, Jamrud Anandez, Arum Adisha Putra Annas, Dicky Atmoko, Indri Aulia, Muti’a Rahma A’yun, Nidha Aulia Qurrata Bambang Subeno Berghuis, Nila Tanyela Bhary, Naradhipa Bilalodin Bilalodin Budi, Indra Busral, Busral Coyanda, John Roni Cyndika Dana Indra Sensuse Dari, Qorinah Wulan DEWI SARTIKA Dhamayanti, Dhamayanti Dwitilas, Fariz Wahyuzan Eka Qadri Nuranti Enrique, Gabriel Faradillah Fatari, Fatari Febrianto, Muhamad Rizki Fridarima, Shanny Geni, Lenggo Gupron, Akhmad Hananto, Djoko Haryadi, Arifin Nur Muhammad Hasnawati Hasnawati Hayati, Atika Trisna Hendrawati, Sulkiah Heri Jodi, Heri Humairoh, Nayu Nur Husin, Husna Sarirah Imelda Saluza, Imelda Indah Permatasari Iskandar Zulkarnaen Jayawarsa, A.A. Ketut Kartika Sari Khusaenah, Nur Kurniawan, Alfin Lastri Widya Astuti, Lastri Widya Laugiwa, Matiin Lukman Hakim Madiabu, Muhammad Jihad Mannix, Ilma Alpha Marcelina, Dona Martawijaya, M. Agus Meganingrum Arista Jiwanggi Ndruru, Sun Theo Constan Lotebulo Nissa, Nuzulul Khairu Nua, Muh. Tri Prasetia Pisgamargareta, Abel Praktino, Budi Prasetyo, Ridho Pratama, Mochamad Jodi Pratiwi, Indah Putri Putri Rizqiyah Putri, Indah Pratiwi Rabiyatul Adawiyah Siregar Rachmadhanti, Elvira Nur Rachmawati, Nur Rama Samudra, M.S Ramadhan, Mustafa Ridho, Muhammad Yusuf Rohmad Salam, Rohmad Rosiana Dwi Saputri, Rosiana Dwi Sampora, Yulianti Saputra, Muklas Ade Sofyan, Muhammad Ihsan Sudaryanto Sumarsih, Rani Sri Sunardi Sunardi Suryati Syazali, Muhammad Rizki Terttiaavini Terttiavini, Terttiavini Zulham Zulham