Utilizing Latent Dirichlet Allocation for Analyzing Topics in Undergraduate Theses-Reference-Cited by-同舟云学术

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Utilizing Latent Dirichlet Allocation for Analyzing Topics in Undergraduate Theses

Published:2023-08-31 Issue: Volume: Page:
ISSN:
Container-title:2023 10th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)
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Author:

Sugiantoro Bambang¹,Humam Achmad Ibrahim¹,Fitriyani Norma Latif²,Alfian Ganjar³,Maarif Muhammad Rifqi⁴,Syafrudin Muhammad⁵

Affiliation:

1. UIN Sunan Kalijaga,Department of Informatics,Yogyakarta,Indonesia

2. Sejong University,Department of Data Science,Seoul,Republic of Korea

3. Vocational College Universitas Gadjah Mada,Department of Electrical Engineering and Informatics,Yogyakarta,Indonesia

4. Tidar University,Department of Industrial Engineering,Magelang,Indonesia

5. Sejong University,Department of Artificial Intelligence,Seoul,Republic of Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10275798/10276392/10277046.pdf?arnumber=10277046

Reference29 articles.

1. Discovering topics and trends in the field of Artificial Intelligence: Using LDA topic modeling

2. Road traffic topic modeling on Twitter using latent dirichlet allocation

3. Implementasi Algoritma Rabin-Karp untuk Pendeteksi Plagiarisme pada Dokumen Tugas Mahasiswa

4. Preprocessing Text untuk Meminimalisir Kata yang Tidak Berarti dalam Proses Text Mining;harjanta;J Inform UPGRIS,2015

5. Latent Dirichlet allocation (LDA) for topic modeling of the CFPB consumer complaints

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