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http://dx.doi.org/10.5392/JKCA.2021.21.11.785

Text Data Analysis Model Based on Web Application  

Jin, Go-Whan (우송대학교 IT융합학부)
Publication Information
The Journal of the Korea Contents Association / v.21, no.11, 2021 , pp. 785-792 More about this Journal
Abstract
Since the Fourth Industrial Revolution, various changes have occurred in society as a whole due to advance in technologies such as artificial intelligence and big data. The amount of data that can be collect in the process of applying important technologies tends to increase rapidly. Especially in academia, existing generated literature data is analyzed in order to grasp research trends, and analysis of these literature organizes the research flow and organizes some research methodologies and themes, or by grasping the subjects that are currently being talked about in academia, we are making a lot of contributions to setting the direction of future research. However, it is difficult to access whether data collection is necessary for the analysis of document data without the expertise of ordinary programs. In this paper, propose a text mining-based topic modeling Web application model. Even if you lack specialized knowledge about data analysis methods through the proposed model, you can perform various tasks such as collecting, storing, and text-analyzing research papers, and researchers can analyze previous research and research trends. It is expect that the time and effort required for data analysis can be reduce order to understand.
Keywords
Text Analysis; Text Collection; Topic Modeling; LDA((Latent Dirichlet Allocation); Web Crawling;
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1 박영욱, 정규엽, "DMR (Dirichlet Multinomial Regression) 토픽모델링을 이용한 온라인 리뷰 빅데이터 기반 고객감성 분석에 관한 연구: 국내 5 성급 호텔의 외국인 이용객 리뷰를 중심으로," 호텔경영학연구논문지, 제30권, 제2호, pp.1-20, 2021.
2 J. Zhu, A. Ahmed, and E. P. Xing, "MedLDA: maximum margin supervised topic models," The Journal of machine Learning research, Vol.13, No.1, pp.2237-2278, 2012.
3 최진욱, 신동원, 이한준, "IT 기업 직원의 만족 및 불만족 요인에 따른 이직률 예측: 토픽모델링과 머신러닝을 활용하여," 한국데이터정보과학회지, 제32권, 제5호, pp.1035-1047, 2021.
4 D. Newman, C. Chemudugunta, P. Smyth, and M. Steyvers, "Analyzing entities and topics in news articles using statistical topic models," International Conference on Intelligence and Security Informatics, Springer, Berlin, Heidelberg, pp.93-104, 2006.
5 H. Jelodar, Y. Wang, C. Yuan, X. Feng, X. Jiang, Y. Li, and L. Zhao, "Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey," Multimedia Tools and Applications, Vol.78, No.11, pp.15169-15211, 2019.   DOI
6 D. M. Blei, "Probabilistic topic models," Communications of the ACM, Vol.55, No.4, pp.77-84, 2012.   DOI
7 D. Mimno, H. Wallach, E. Talley, M. Leenders, and A. McCallum, "Optimizing semantic coherence in topic models," In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pp.262-272, 2011.
8 채호근, 이기현, 이주연, "토픽모델링 분석 기법을 활용한 국내외 금융보안 분야 연구동향 분석," 한국산업정보학회논문지, 제26권, 제1호, pp.83-95, 2021.   DOI
9 김민성, 정형록, 김미옥, 박진하, "한국 관리회계 사례 논문의 연구동향," 한국관리회계학회논문지, 제15권, 제1호, pp.71-112, 2015.
10 김상범, 김효관, "4차산업 혁명과 빅데이터 기반 기술," 대한전자공학회지, 제46권, 제11호, pp.17-25, 2019.
11 R. Alghamdi and K. Alfalqi, "A survey of topic modeling in text mining," International Journal of Advanced Computer Science and Applications (IJACSA), Vol.6, No.1, pp.147-153, 2015.
12 S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman, "Indexing by latent semantic analysis," Journal of the American society for information science, Vol.41, No.6, pp.391-407, 1990.   DOI
13 D. M. Blei, A. Y. Ng, and M. I. Jordan, "Latent dirichlet allocation," The Journal of machine Learning research, Vol.3, pp.993-1022, 2003.
14 C. Wang and D. M. Blei, "Collaborative topic modeling for recommending scientific articles," In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pp.448-456, 2011.
15 권혜진, 전재균, "텍스트 마이닝 기법을 통한 숙박공유서비스 에어비앤비 (Airbnb)에 대한 탐색적 연구," 한국조리학회논문지, 제26권, 제8권, pp.143-153, 2020.
16 윤지혜, 이종화, "토픽모델링을 활용한 CSR 키워드 트렌드 분석," 한국인터넷전자상거래학회논문지, 제21권, 제5호, pp.73-91, 2021.
17 김원식, 김두산, "LDA 토픽모델링을 활용한 호텔등급별 서비스품질 요인도출," 한국무역연구원논문지, 제16권, 제5호, pp.779-791, 2020.
18 H. Zhang, B. Chen, Y. Cong, D. Guo, H. Liu, and M. Zhou, "Deep autoencoding topic model with scalable hybrid Bayesian inference," IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.1-17, 2020.
19 C. Wang, B. Chen, and M. Zhou, "Multimodal Poisson gamma belief network," In Proceedings of the AAAI Conference on Artificial Intelligence, Vol.32, No.1, pp.2492-2499, 2018.
20 D. M. Blei and J. D. Lafferty, "A correlated topic model of science," The annals of applied statistics, Vol.1, No.1, pp.17-35, 2007.   DOI
21 문성현, 정세환, 지석호, "Latent Dirichlet Allocation 기법을 활용한 해외건설시장 뉴스기사의 토픽 모델링(Topic Modeling)," 대한토목학회논문지, 제38권, 제4호, pp.595-599, 2018.
22 S. Sun, C. Luo, and J. Chen, "A review of natural language processing techniques for opinion mining systems," Information fusion, Vol.36, pp.10-25, 2017.   DOI
23 Z. Chen, A. Mukherjee, and B. Liu, "Aspect extraction with automated prior knowledge learning," In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, Vol.1, pp.347-358, 2014.