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Journal articles on the topic 'Descriptive Text Mining'

Author: Grafiati

Published: 18 April 2022

Last updated: 18 July 2025

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1

Shin, JongHo, and Jaewon Choi. "Text mining Analysis of College Students’ Descriptive Course Evaluation." Korean Association For Learner-Centered Curriculum And Instruction 19, no. 16 (2019): 77–99. http://dx.doi.org/10.22251/jlcci.2019.19.16.77.

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Teng, Shasha, Kok Wei Khong, Saeed Pahlevan Sharif, and Amr Ahmed. "YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis." JMIR Public Health and Surveillance 6, no. 4 (2020): e19618. http://dx.doi.org/10.2196/19618.

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Background Poor nutrition and food selection lead to health issues such as obesity, cardiovascular disease, diabetes, and cancer. This study of YouTube comments aims to uncover patterns of food choices and the factors driving them, in addition to exploring the sentiments of healthy eating in networked communities. Objective The objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviors in online communities and provide insight into YouTube video commenters’ perceptions and sentiments of healthy eating through text mining techniques. Methods This

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Lee, In. "Analysis of Insider Threats in the Healthcare Industry: A Text Mining Approach." Information 13, no. 9 (2022): 404. http://dx.doi.org/10.3390/info13090404.

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To address rapidly growing data breach incidents effectively, healthcare providers need to identify various insider and outsider threats, analyze the vulnerabilities of their internal security systems, and develop more appropriate data security measures against the threats. While there have been studies on trends of data breach incidents, there is a lack of research on the analysis of descriptive contents posted on the data breach reporting website of the U.S. Department of Health and Human Services (HHS) Office for Civil Rights (OCR). Hence, this study develops a novel approach to the analysi

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Yunarfi, Geovaldo Reggie, Ricky Simdy, and Jackson. "Implementasi Text Mining untuk Mengetahui Kata Abreviasi dalam Percakapan Media Sosial." Journal of Digital Ecosystem for Natural Sustainability 1, no. 2 (2021): 78–83. https://doi.org/10.63643/jodens.v1i2.43.

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Social media are technology that allow sharing or exchange of information, ideas, interests, etc., via virtual communities and networks. Social media is often use for chatting either private chat or commenting on posts, and most frequently used application in Indonesia such as Facebook, WhatsApp, Instagram, Twitter, and so on. So far, peoples are typing using abbreviations as habit instead using full word and thus cause misunderstanding for others. Descriptive qualitative method was used to collect data. Text mining is a data science technique which mine data in the form of text and look for w

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Kutela, Boniphace, Richard Dzinyela, Henrick Haule, Abbas Sheykhfard, and Kelvin Msechu. "Leveraging autonomous vehicles crash narratives to understand the patterns of parking-related crashes." Traffic Safety Research 4 (July 5, 2023): 000033. http://dx.doi.org/10.55329/fiqq8731.

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Autonomous vehicles (AVs) parking has been a subject of interest from various researchers; however, the focus has been on the parking demand, algorithm, and policies, while the safety aspect has received less attention, perhaps due to the lack of AV crash data. This study evaluated the magnitude and pattern of AV parking-related crashes that occurred between January 2017 and August 2022 in California. The study applied descriptive analysis, unsupervised text mining, and supervised text mining (Support Vector Machine, Naïve Bayes, Logitboost, Random Forest, and Neural network) with resampling t

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Qiu, Longtian, Shan Ning, and Xuming He. "Mining Fine-Grained Image-Text Alignment for Zero-Shot Captioning via Text-Only Training." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 5 (2024): 4605–13. http://dx.doi.org/10.1609/aaai.v38i5.28260.

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Image captioning aims at generating descriptive and meaningful textual descriptions of images, enabling a broad range of vision-language applications. Prior works have demonstrated that harnessing the power of Contrastive Image Language Pre-training (CLIP) offers a promising approach to achieving zero-shot captioning, eliminating the need for expensive caption annotations. However, the widely observed modality gap in the latent space of CLIP harms the performance of zero-shot captioning by breaking the alignment between paired image-text features. To address this issue, we conduct an analysis

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ALtom Shihabeldeen, Hassabelrasul Yusuuf. "Using Text Mining to Predicate Exchange Rates with Sentiment Indicators." Journal of Business Theory and Practice 7, no. 2 (2019): p60. http://dx.doi.org/10.22158/jbtp.v7n2p60.

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Recent innovations in text mining facilitate the use of novel data for sentiment analysis related to financial markets, and promise new approaches to the field of behavioral finance. Traditionally, text mining has allowed a near-real time analysis of available news feeds. The recent dissemination of web 2.0 has seen a drastic increase of user participation, providing comments on websites, social networks and blogs, creating a novel source of rich and personal sentiment data potentially of value to behavioral finance. This study explores the efficacy of using novel sentiment indicators from Mar

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Tsimaras, Dimitrios, Emmanouil Zoulias, and Chryssi Vitsilaki. "Evaluation of Vocational E-Learning Seminars." WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION 20 (February 22, 2023): 32–36. http://dx.doi.org/10.37394/232010.2023.20.5.

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The fourth industrial revolution emerges from a demanding need for reskilling and upskilling every active working person. Furthermore, the European Commission included key policy instruments for resilience, social fairness, and sustainable competitiveness in the European Skills Agenda. Distance training and education programs are key factors to succeed in the targets mentioned above. Due to the o COVID-19 pandemic, already 30% of the total education in European countries has further expanded. As a result, online evaluation approaches are more than necessary. Various methodologies have been app

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Yoon, Sora. "Accounting Studies Using Text Analysis : Now and Future." Korean Accounting Information Association 23, no. 4 (2023): 119–51. http://dx.doi.org/10.29189/kaiajfai.23.4.6.

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[Purpose] The purpose of this study is to examine prior literature using text mining analysis techniques in the accounting area for identifying current research themes, to present other data analysis techniques, and to provide directions for future research and practice. [Methodology] For this study, I use the Systematic Literature Review(SLR) methodology adopted in Schmitz and Leoni(2019). The results are obtained by entering keywords of “text analysis’ and “accounting” in Google Scholar, and the prior researches reviewed in this paper are selected among them and their references, mainl

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Longhini, Tatielle Menolli, Marcelo Azevedo Costa, and Bruno de Almeida Vilela. "Satscan regression: a bibliometric study based on text mining procedures." Caderno Pedagógico 22, no. 6 (2025): e15717. https://doi.org/10.54033/cadpedv22n6-214.

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The scan statistic has been a methodology widely applied for spatial and space-time cluster detection. This is because, by identifying areas with a significant concentration of points, we gain evidence for the analysis of underlying phenomena. This article aims to conduct a bibliometric study on spatial scan regression. Spatial scan regression includes correlation between the outcome and potential regressor variables into the cluster detection. The bibliometric study applies a robust literature search methodology, using Web of Science and Scopus as the main databases. Thus, the most relevant a

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Xu, Penghao, Zhengxing Peng, and Lu Deng. "Analysis of China's Intelligent Logistics Policies based on Text Mining." International Journal of Social Sciences and Public Administration 2, no. 3 (2024): 19–31. http://dx.doi.org/10.62051/ijsspa.v2n3.03.

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Based on text mining technology, this paper provides a comprehensive analysis of China's intelligent logistics policies. Through the descriptive statistical analysis of the annual release volume, types and subjects of policy texts, the dynamic trends, dominant forms and major sectors of policy releases are revealed. Using the TF-IDF algorithm to extract keywords and combining with the LDA thematic model analysis, it is found that the key areas of the policies include: improving the service capacity of enterprises, cold chain logistics construction, supply chain synergy, green standardisation,

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Slater, Stefan, Srećko Joksimović, Vitomir Kovanovic, Ryan S. Baker, and Dragan Gasevic. "Tools for Educational Data Mining." Journal of Educational and Behavioral Statistics 42, no. 1 (2016): 85–106. http://dx.doi.org/10.3102/1076998616666808.

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In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will highlight the utility that these tools have with respect to common data preprocessing and analysis steps in a typical research project as well as more descriptive information such as price point and user-friendliness. We will also highlight niche tools in th

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Wahyu Ananda Putri Aulia, Dea. "Text Mining dari Jurnal Teknologi Pendidikan Menggunakan Term Frequency Matrix." Sciencestatistics: Journal of Statistics, Probability, and Its Application 3, no. 1 (2025): 15–28. https://doi.org/10.24127/sciencestatistics.v3i1.5989.

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Penelitian ini bertujuan untuk menganalisis kata-kata yang paling sering muncul dalam beberapa artikel yang diterbitkan oleh Jurnal Teknologi Pendidikan menggunakan pendekatan term frequency matrix. Melalui teknik text mining, data dari abstrak artikel diolah untuk mengidentifikasi kata-kata kunci dan memahami pola penelitian dalam bidang teknologi pendidikan. Analisis dilakukan pada tiga edisi terakhir jurnal, yaitu Vol. 7 No. 3, Vol. 7 No. 4, dan Vol. 8 No. 1, dengan memanfaatkan metode matematika berbasis frekuensi kata. Data diolah melalui tahapan preprocessing, tokenisasi, dan pembuatan m

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Rakhmetullina, Zhenisgul, Saule Belginova, Alibekkyzy Karlygash, Aigerim Ismukhamedova, and Shynar Tezekpaeva. "Research and implementation of the medical text analysis algorithm for predicting mortality." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 3 (2024): 1965. http://dx.doi.org/10.11591/ijeecs.v34.i3.pp1965-1977.

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Mortality prediction has a role to play in the development of a descriptive measure of the quality of care that provides a fair and equitable means of comparing and evaluating hospitals. This article describes a study of a medical text analysis algorithm for mortality prediction that used big data in the form of unstructured medical notes. The article describes the concept of using text mining technology for medical systems, a method for preprocessing medical data to predict patient mortality, an algorithm for predicting patient deaths based on the logistic regression classifier and presents a

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Rakhmetullina, Zhenisgul, Saule Belginova, Alibekkyzy Karlygash, Aigerim Ismukhamedova, and Shynar Tezekpaeva. "Research and implementation of the medical text analysis algorithm for predicting mortality." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 3 (2024): 1965–77. https://doi.org/10.11591/ijeecs.v34.i3.pp1965-1977.

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Mortality prediction has a role to play in the development of a descriptive measure of the quality of care that provides a fair and equitable means of comparing and evaluating hospitals. This article describes a study of a medical text analysis algorithm for mortality prediction that used big data in the form of unstructured medical notes. The article describes the concept of using text mining technology for medical systems, a method for preprocessing medical data to predict patient mortality, an algorithm for predicting patient deaths based on the logistic regression classifier and presents a

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Chen, Ziyang, Cristhiam Gurdian, Chetan Sharma, Witoon Prinyawiwatkul, and Damir D. Torrico. "Exploring Text Mining for Recent Consumer and Sensory Studies about Alternative Proteins." Foods 10, no. 11 (2021): 2537. http://dx.doi.org/10.3390/foods10112537.

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Increased meat consumption has been associated with the overuse of fresh water, underground water contamination, land degradation, and negative animal welfare. To mitigate these problems, replacing animal meat products with alternatives such as plant-, insect-, algae-, or yeast-fermented-based proteins, and/or cultured meat, is a viable strategy. Nowadays, there is a vast amount of information regarding consumers’ perceptions of alternative proteins in scientific outlets. Sorting and arranging this information can be time-consuming. To overcome this drawback, text mining and Natural Language P

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Kotozaki, Yuka. "An Exploratory Descriptive Study: Emotional Extraction of Postpartum Women Who Engaged in Horticulture Activities by Text Mining." Psychology 11, no. 10 (2020): 1481–92. http://dx.doi.org/10.4236/psych.2020.1110094.

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Kuncoro, Abdi Sri. "Analisis Wacana Kritis Pemberitaan Penolakan Tambang Andesit di Desa Wadas pada Tempo.co." Mediator: Jurnal Komunikasi 15, no. 1 (2022): 15–27. http://dx.doi.org/10.29313/mediator.v15i1.9522.

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This study explains the dimension of the Teun A van Dijk model in online text news entitled "Rejecting the Andesite Mining in Wadas Village" by Tempo.co. Tempo's online newspaper provided survey data and data sources in text news entitled Rejecting the Andesite Mining in Wadas Village. The data collection technique in this research is used a descriptive-analytical documentation method with a critical discourse analytical approach of the Teun A van Dijk models. Investigation in Teun Van Djik's theory consists of three dimensions. Those three dimensions are superstructure, macrostructure, and mi

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Park, Jin-seo. "SUPPORTING AIR TRANSPORT POLICIES USING BIG DATA ANALYTICS: A DESCRIPTIVE APPROACH BASED EMERGING TREND ANALYSIS." Journal of Air Transport Studies 8, no. 1 (2017): 51–72. http://dx.doi.org/10.38008/jats.v8i1.40.

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Qualitative research methods based on literature review or expert judgement have been used to find core issues, analyze emerging trends and discover promising areas for the future. Deriving results from large amounts of information under this approach is both costly and time consuming. Besides, there is a risk that the results may be influenced by the subjective opinion of experts. In order to make up for such weaknesses, the analysis paradigm for choosing future emerging trend is undergoing a shift toward mplementing qualitative research methods along with quantitative research methods like t

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Khandale, Shreyas, Prathamesh Patil, and Rohan Patil. "Amazon Fine Food Review Analysis." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (2023): 23–27. http://dx.doi.org/10.22214/ijraset.2023.55930.

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Abstract: This paper presents a comprehensive examination of the Amazon Fine Food Reviews dataset, encompassing both descriptive and predictive analyses. The study involved employing various text mining techniques, dimensionality reduction approaches, and linear regression models to forecast review scores. Ultimately, a model was developed that achieved a Root Mean Square Error (RMSE) of 1.0936, enabling accurate predictions for new reviews.

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Ragil, Muhammad. "Analisa Sentimen Terhadap Transisi Dari Work From Home ke Work From Office Menggunakan Metode Text Mining Dan TF-IDF." Bulletin of Data Science 3, no. 1 (2023): 160–68. https://doi.org/10.47065/bulletinds.v3i1.5694.

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The implementation of the WFH(Work From Home) and WFO(Work From Office) work schemes has problems related to the adjustment of the work system by workers. Every company or industrial world always prioritizes the value of productivity in any circumstances to prevent a significant decrease in profits. In this sentiment analysis, the researcher uses the Text Mining and TF-IDF methods based on data collected from the Orange DataMining Twitter application by entering the Twitter Key Secret Token API to retrieve the data from the Twitter social networking platform. And continued with the Text Mining

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Ramesh, Y. V., and S. Shanmukh Rao. "MOOC Data Analytics through Text Mining-An Innovative Approach to Learning Improvement." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 4802–6. http://dx.doi.org/10.22214/ijraset.2023.54508.

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Abstract: The COVID-19 pandemic has brought about significant changes in the perception of education, with Massive Open Online Course (MOOC) providers like Coursera witnessing a surge in millions of new user registrations on their platforms. However, despite the prevalence of online review systems in various industries, the MOOC ecosystem lacks a standardized or fully decentralized review system. We believe that there is an opportunity to utilize existing open MOOC reviews to create userfriendly and transparent reviewing systems, enabling learners to easily identify the top courses available.

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Trinko, David, Emily Porter, Jamie Dunckley, Thomas Bradley, and Timothy Coburn. "Combining Ad Hoc Text Mining and Descriptive Analytics to Investigate Public EV Charging Prices in the United States." Energies 14, no. 17 (2021): 5240. http://dx.doi.org/10.3390/en14175240.

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Electric vehicle (EV) charging infrastructure is present all over the United States, but charging prices vary greatly, both in amount and in the methods by which they are assessed. For this paper, we interpret and analyze charging price information from PlugShare, a crowd-sourced EV charging data platform. Because prices in these data exist in a semi-structured textual format, an ad hoc text mining approach is used to extract quantitative price information. Descriptive analytics of the processed dataset demonstrate how the prices of EV charging vary with charging level (Direct Current Fast Cha

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Arafik, Arafik, Restu Juniah, and Mohammad Zulkarnain. "Safety And Health Implementation Study Work (K3) In Coal Mining Companies (Case Study: PT. XYZ)." Indonesian Journal of Environmental Management and Sustainability 3, no. 3 (2019): 75–79. http://dx.doi.org/10.26554/ijems.2019.3.3.75-79.

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This study aims to analyze the implementation of occupational safety and health (K3) in the coal mining company PT XYZ, Analyze and identify the factors that influence the implementation of occupational safety and health (K3) in the mining company PT XYZ. This research is a descriptive qualitative and quantitative research approach. Primary data obtained from respondents are used as a means to obtain information or data carried out by field surveys through direct observation and interviews with respondents in the company and secondary data obtained from PT XYZ collected and compiled according

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Aversa, Dario, Nino Adamashvili, Mariantonietta Fiore, and Alessia Spada. "Scoping Review (SR) via Text Data Mining on Water Scarcity and Climate Change." Sustainability 15, no. 1 (2022): 70. http://dx.doi.org/10.3390/su15010070.

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Climate change is causing the risk of weather events and instable water accessibility, making water insufficiency a serious problem. According to the 2022 Intergovernmental Panel on Climate Change (IPCC), 70% of extreme weather events such as droughts and floods have been water-related in the last 15 years. Since the climate change processes are speeding up, this percentage is expected to increase. A plethora of researchers have been working on the correlation between water scarcity and climate change. The purpose of this paper is to examine the published research dealing with water scarcity a

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Cvetkoska, Violeta, Igor Ivanovski, and Marija Tasheva. "Literature survey on DEA in the insurance industry with a focus on identification of research hotspots with text mining." Journal of corporate governance, insurance and risk management 8, no. 2 (2021): 114–30. http://dx.doi.org/10.51410/jcgirm.8.2.8.

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DEA is a frequently used non-parametric methodology for measuring the relative efficiency of Decision-Making Units (DMUs) that use the same inputs to produce the same outputs. Emrouznejad and Yang (2018) provided a literature survey on DEA with 10,300 peer-reviewed journal articles from 1978 to the end of 2016. Our article focuses on DEA applications in the insurance industry in convergence with the existing relevant literature as Kaffash et al (2020), who have surveyed 132 DEA articles in the insurance industry for the period from 1993 to 2018. We include particular keyword analyses necessary

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SAE-LIM, Patipan. "Modeling Enterprise Risk Management Ecosystems Using Text Analytics." Foundations of Management 16, no. 1 (2024): 391–406. https://doi.org/10.2478/fman-2024-0024.

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Abstract In recent years, a paradigm shift in risk management has altered in a holistic way, which we call Enterprise Risk Management (ERM). ERM solves the limitations of Traditional Risk Management (TRM). Although firms perceive several benefits of ERM, the successful implementation of ERM rests upon institutional and contingency factors. The ERM approach then seeks to integrate the core system and processes of the firm rather than acting through silo perspective. With this in mind, this research applies text mining techniques to analyze bibliometric data from SCOPUS to propose the suitable E

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Utari, Suci. "Penerapan Algoritma Rought Set Untuk Memprediksi Jumlah Permintaan Produk." Bulletin of Artificial Intelligence 1, no. 1 (2022): 1–7. http://dx.doi.org/10.62866/buai.v1i1.1.

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Data Mining is a term used to describe the discovery of knowledge in databases. Data mining is a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify useful information and tied knowledge from large databases. Demand is a number of goods purchased or requested at a certain price and time. Demand is related to consumer desires for goods and services to be fulfilled. And the tendency of consumer demand for goods and services is unlimited. According to the everyday sense of demand is defined in absolute terms, namely the num

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Vairinhos, Valter Martins, Luís Agonia Pereira, Florinda Matos, Helena Nunes, Carmen Patino, and Purificación Galindo-Villardón. "Framework for Classroom Student Grading with Open-Ended Questions: A Text-Mining Approach." Mathematics 10, no. 21 (2022): 4152. http://dx.doi.org/10.3390/math10214152.

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The purpose of this paper is to present a framework based on text-mining techniques to support teachers in their tasks of grading texts, compositions, or essays, which form the answers to open-ended questions (OEQ). The approach assumes that OEQ must be used as a learning and evaluation instrument with increasing frequency. Given the time-consuming grading process for those questions, their large-scale use is only possible when computational tools can help the teacher. This work assumes that the grading decision is entirely a teacher’s task responsibility, not the result of an automatic gradin

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Jiang, Yunhan. "Statistical and sentiment analysis based on comments of skin care products." Applied and Computational Engineering 47, no. 1 (2024): 177–85. http://dx.doi.org/10.54254/2755-2721/47/20241294.

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With the continuous development of the Internet economy and the strong promotion in various aspects, the rise of new domestic brands has led to an increasing number of consumers paying attention to and purchasing cosmetics online. Grasping the pulse of the times in this context is a crucial key to understanding the Internet economy. This paper first crawled the product links of the JD.com skin care essence category, randomly selecting 100 products. Subsequently, a total of 49,560 comments were crawled for the selected products. Furthermore, employing text mining techniques, this paper conducts

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Indriani, Indriani, Ponirin Ponirin, Maskuri Sutomo, and Faruq Lamusa. "Eksplorasi Faktor yang di Pertimbangkan Pelanggan Menggunakan Jasa Percetakan CV. Oke Printing di Kota Palu." Jurnal Media Wahana Ekonomika 22, no. 1 (2025): 1–8. https://doi.org/10.31851/jmwe.v22i1.18436.

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ABSTRAK Penelitian ini bertujuan untuk mengeksplorasi faktor yang dipertimbangkan pelanggan menggunakan jasa percetakan CV. Oke printing di Kota Palu. Metode yang di gunakan adalah kualitatif deskriptif. Sampel dipilih menggunakan teknik purposive sampling dengan melibatkan 30 responden pelanggan percetakan CV. Oke printing. Teknik pengumpulan data dilakukan melalui wawancara dan observasi. Analisis data menggunakan model text mining di orange dangan teknik model interaktif. Hasil penelitian ditemukan tiga tema utama yang dipertimbangkan pelanggan menggunakan jasa, yakni harga, kualitas layana

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Utari, Suci. "Penerapan Algoritma Rought Set Untuk Memprediksi Jumlah Permintaan Produk." Bulletin of Data Science 1, no. 2 (2022): 73–79. https://doi.org/10.47065/bulletinds.v1i2.1362.

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Demand is a number of goods purchased or requested at a certain price and time. Demand is related to consumer desires for goods and services to be fulfilled. And trends Consumer demand for goods and services is unlimited. In everyday terms, demand is defined in absolute terms, namely the amount of goods needed. This way of thinking is based on the idea that humans have needs. For this need, the individual has a demand for goods, the more residents of a country, the greater the public's demand for goods. Rapid Miner is open source software. Rapid Miner is a solution for analyzing data mining, t

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Goswami, Mausumi, and B.S Purkayastha. "AN EMPIRICAL ANALYSIS OF SIMILARITY MEASURES FOR UNSTRUCTURED DATA." COMPUSOFT: An International Journal of Advanced Computer Technology 08, no. 08 (2019): 3302–6. https://doi.org/10.5281/zenodo.14832795.

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With fast growth in size of digital text documents over internet and digital repositories, the pools of digital document is piling up day by day. Due to this digital revolution and growth, an efficient and effective technique is required to handle such an enormous amount of data. It is extremely important to understand the documents properly to mine them. To find coherence among documents text similarity measurement pays a humongous role. The goal of similarity computation is to identify cohesion among text documents and to make the text ready for the required applications such as document org

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Goswami, Mausumi, and B.S Purkayastha. "AN EMPIRICAL ANALYSIS OF SIMILARITY MEASURES FOR UNSTRUCTURED DATA." COMPUSOFT: An International Journal of Advanced Computer Technology 08, no. 08 (2019): 3302–6. https://doi.org/10.5281/zenodo.14832840.

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With fast growth in size of digital text documents over internet and digital repositories, the pools of digital document is piling up day by day. Due to this digital revolution and growth, an efficient and effective technique is required to handle such an enormous amount of data. It is extremely important to understand the documents properly to mine them. To find coherence among documents text similarity measurement pays a humongous role. The goal of similarity computation is to identify cohesion among text documents and to make the text ready for the required applications such as document org

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Bach, Mirjana Pejić, Mislav Ante Omazić, and Ivan Miloloža. "Success determinants of projects of business software implementation: Research framework." Croatian Regional Development Journal 2, no. 2 (2021): 1–16. http://dx.doi.org/10.2478/crdj-2021-0010.

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Abstract The experience of many organizations so far has shown that the risk of failure of the software implementation project is high, and in order to reduce this risk, significant efforts have been made so far to implement the project management methodology. However, research to date shows that, despite improvements in project management, a relatively significant number of projects still fail by some of the performance criteria. A methodology is proposed that includes: (i) analysis of previous research; (ii) design a research instrument to measure project performance and define key determina

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Ardhani, Belindha Ayu, Nur Chamidah, and Toha Saifudin. "Sentiment Analysis Towards Kartu Prakerja Using Text Mining with Support Vector Machine and Radial Basis Function Kernel." Journal of Information Systems Engineering and Business Intelligence 7, no. 2 (2021): 119. http://dx.doi.org/10.20473/jisebi.7.2.119-128.

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Background: The introduction of Kartu Prakerja (Pre-employment Card) Programme, henceforth KPP, which was claimed to have launched in order to improve the quality of workforce, spurred controversy among members of the public. The discussion covered the amount of budget, the training materials and the operations brought out various reactions. Opinions could be largely divided into groups: the positive and the negative sentiments.Objective: This research aims to propose an automated sentiment analysis that focuses on KPP. The findings are expected to be useful in evaluating the services and faci

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Kesgin, Muhammet, Rajendran Murthy, and Rick Lagiewski. "Profiling food festivals by type, name and descriptive content: a population level study." British Food Journal 124, no. 2 (2021): 530–49. http://dx.doi.org/10.1108/bfj-04-2021-0412.

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PurposeThis research aims to classify and describe food festivals and examine the patterns in food festival naming and festival descriptions in online media.Design/methodology/approachThis research represents the first population-level empirical examination of food festivals in the United States using a purpose-built dataset (N = 2,626). Methodology includes text mining to examine food festival communications.FindingsFood festival size varies across local and regional spheres within the country. Food festivals employ geographical (place-, destination-based) associations in their names. Food fe

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Evangelista, Chiara, Marco Milanesi, Daniele Pietrucci, Giovanni Chillemi, and Umberto Bernabucci. "Enteric Methane Emission in Livestock Sector: Bibliometric Research from 1986 to 2024 with Text Mining and Topic Analysis Approach by Machine Learning Algorithms." Animals 14, no. 21 (2024): 3158. http://dx.doi.org/10.3390/ani14213158.

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Methane (CH4) from livestock, particularly enteric CH4 emission (EME), is one contributor to greenhouse gas emissions and climate change. This review analyzed 1294 scientific abstracts on EME in ruminants from 1986 to May 2024, using Scopus® data. Descriptive statistics, text mining, and topic analysis were performed. Publications on EME have risen significantly since 2005, with the Journal of Dairy Science being the most frequent publisher. Most studies (82.1%) were original research, with Northern Hemisphere countries leading in publication numbers. The most frequent terms were “milk”, “cow”

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Bozkurt, Aras, Hasan Ucar, Gurhan Durak, and Sahin Idin. "The current state of the art in STEM research: A systematic review study." Cypriot Journal of Educational Sciences 14, no. 3 (2019): 374–83. http://dx.doi.org/10.18844/cjes.v14i3.3447.

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In the 21st century, when the knowledge-based economy is steering improvement and development, STEM education has gained increasing momentum and importance. This study aims to identify the current trends in STEM education, and also explores and identifies research trends and patterns in articles published between 2014 and 2016 on STEM education through a systematic review study. The research findings indicate that interest in STEM education in scholarly venues has witnessed a marked increase since 2014, with researchers preferring mostly quantitative, conceptual/descriptive, qualitative, mixed

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Previti, Annalisa, Vito Biondi, Mehmet Erman Or, Bengü Bilgiç, Michela Pugliese, and Annamaria Passantino. "Text Mining and Topic Analysis for Ostriches’ Welfare Based on Systematic Literature Review from 1983 to 2023." Veterinary Sciences 11, no. 10 (2024): 477. http://dx.doi.org/10.3390/vetsci11100477.

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Ostriches can be utilized as multipurpose animals suitable for producing meat, eggs, feathers, and leather. This growing interest in ostrich farming leads to an increased demand for comprehensive information on their management. But, little attention is paid to the consequences for their welfare. The study aimed to perform a research literature analysis on ostriches’ welfare using the text mining (TM) and topic analysis (TA) methods. It identifies prevailing topics, summarizes their temporal trend within the last forty years, and highlights potential research gaps. According to PRISMA guidelin

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Previti, Annalisa, Vito Biondi, Annamaria Passantino, Mehmet Erman Or, and Michela Pugliese. "Canine Bacterial Endocarditis: A Text Mining and Topics Modeling Analysis as an Approach for a Systematic Review." Microorganisms 12, no. 6 (2024): 1237. http://dx.doi.org/10.3390/microorganisms12061237.

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Bacterial endocarditis (BE) is a severe infection of the endocardium and cardiac valves caused by bacterial agents in dogs. Diagnosis of endocarditis is challenging due to the variety of clinical presentations and lack of definitive diagnostic tests in its early stages. This study aims to provide a research literature analysis on BE in dogs based on text mining (TM) and topic analysis (TA) identifying dominant topics, summarizing their temporal trend, and highlighting any possible research gaps. A literature search was performed utilizing the Scopus® database, employing keywords pertaining to

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Izza, Nadia Nurul, Anita Priantina, and Aam Slamet Rusydiana. "UTILIZING TWITTER DATA TO UDERSTAND GLOBAL HALAL INDUSTRY TRENDS AND DEVELOPMENTS IN THE DIGITAL ERA." Airlangga International Journal of Islamic Economics and Finance 6, no. 02 (2023): 106–29. http://dx.doi.org/10.20473/aijief.v6i02.50700.

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Abstract The research aims to identify and collect issues related to the halal industry discussed by users' activities, sentiments, and content on Twitter. The method used involved collecting 135,050 Twitter conversations over a two-year period from July 21, 2021, to March 15, 2023, utilizing the Drone Emprit Academic (DEA) machine. Text data mining techniques were employed with the assistance of the DEA system, which included sentiment analysis, Social Network Analysis (SNA), and other descriptive analyses. The research findings indicate that the highest number of tweets related to the

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Sinaga, Titin Handayani, Anjar Wanto, Indra Gunawan, Sumarno Sumarno, and Zulaini Masruro Nasution. "Implementation of Data Mining Using C4.5 Algorithm on Customer Satisfaction in Tirta Lihou PDAM." Journal of Computer Networks, Architecture, and High-Performance Computing 3, no. 1 (2021): 9–20. http://dx.doi.org/10.47709/cnahpc.v3i1.923.

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This application applies the C4.5 Algorithm to decide customer satisfaction, the C4.5 algorithm is one of the algorithms used to classify or segment, or group and it is predictive. This type of research is a classification with the concept of data mining involving 150 customers of PDAM Tirta Lihou in Totap Majawa Kab. Simalungun can be categorized as: "Satisfied and Dissatisfied". The meaning of Data Mining is an interdisciplinary subfield of computer science and statistics with the overall objective of extracting information (with intelligent methods) from data sets and converting information

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Aisyah, Aisyah, Anang M. Legowo, and Muflihatul Muniroh. "Literature review: Paparan merkuri (Hg) pada anak stunting di area pertambangan emas." Jurnal SAGO Gizi dan Kesehatan 5, no. 3A (2024): 587. http://dx.doi.org/10.30867/gikes.v5i3a.1713.

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Background: Mercury (Hg) is used by small-scale gold miners to extract gold. Mercury waste is dangerous and toxic because it pollutes the environment and living creatures. Mercury can accumulate in the body through the food chain, air and air. Children who are exposed to mercury are associated with a risk of various health problems that can result in stunting.Objective: The aim of writing this literature review is to identify exposure to mercury (Hg) in stunted children.Method: This research is in the form of descriptive analysis. This research took the form of a literature review, article syn

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Mubaroq, Afiq Chamim, Ascaryan Rafinda, Christina Tri Setyorini, Ihsan Nasihin, Emir Surya Rahmajati, and Osama Alhendi. "EXPLORING THE PARADOX OF MSME GROWTH DURING RAMADHAN." EL DINAR: Jurnal Keuangan dan Perbankan Syariah 13, no. 1 (2025): 53–76. https://doi.org/10.18860/ed.v13i1.29185.

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This study aims to examine the dual impact of Ramadan on MSMEs in Indonesia, where increased consumer demand coincides with supply chain disruptions, rising costs, and logistical challenges. The research employs a qualitative descriptive approach with text mining techniques to collect data from various trusted online media sources. The findings indicate that while Ramadan creates significant economic opportunities for MSMEs, challenges remain in meeting market demand. This study highlights the paradoxical nature of this period, underscoring the need for strategic interventions from stakeholder

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Flávio Leite Rodrigues, Galileu Batista de Sousa, and Marcelo de Andrade Lima Maia. "What is forensic chemistry research in Brazil made of? A descriptive and topic modeling analysis of CAPES theses and dissertations." International Journal of Science and Research Archive 15, no. 2 (2025): 695–705. https://doi.org/10.30574/ijsra.2025.15.2.1372.

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This article investigates the landscape of forensic chemistry research in Brazil by analyzing 118 master's and doctoral theses and dissertations retrieved from the CAPES Thesis and Dissertation Catalog using the keyword “química forense”. Through text mining and Latent Dirichlet Allocation (LDA) topic modeling, we identified thematic patterns and institutional trends in graduate-level research. Descriptive statistics revealed a concentration of academic production in southeastern Brazil and a predominance of master’s theses. The topic modeling analysis, applied to both unigrams and n-grams, un

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Das, Subasish, Anandi Dutta, and Marcus A. Brewer. "Case Study of Trend Mining in Transportation Research Record Articles." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (2020): 1–14. http://dx.doi.org/10.1177/0361198120936254.

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This study employs two topic models to perform trend mining on an abundance of textual data to determine trends in research topics from immense collections of unstructured documents over the years. This study collected data from the titles and abstracts of the papers published in Transportation Research Record: Journal of the Transportation Research Board, since 1974. The content of these papers was ideal for examining research trends in various fields of research because it contains large textual data. In previous studies, exploratory analysis tools such as text mining were used to provide de

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Begum, Safira, and Sunita S. Padmannavar. "Analysis and Prediction of Higher Education Learners’ Mindset Using Data Mining Tool and Techniques." Journal of Computational and Theoretical Nanoscience 17, no. 9 (2020): 4344–49. http://dx.doi.org/10.1166/jctn.2020.9074.

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With advent of smart-phones and internet first approach, large amounts of data is generated and collected everyday which is considered as Big Data. Analyzing and making sense out of such data is very important but challenging as well, due to its complexity. The knowledge is hidden in the data and can be extracted through Data mining techniques. The purpose of this descriptive research study is to evaluate and predict the mindset of rural and urban students with text analytics and visualization capabilities in the Orange tool. As part of the study a group of undergraduate students from differen

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Gabud, Roselyn, Sandra Yap, Riza Batista-Navarro, and Sophia Ananiadou. "Developing a knowledge base on the habitats and reproductive conditions of Dipterocarps through information extraction." Biodiversity Information Science and Standards 1 (August 7, 2017): e20066. https://doi.org/10.3897/tdwgproceedings.1.20066.

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Dipterocarps, belonging to the family <em>Dipterocarpaceae</em>, are economically and ecologically important in the Philippines due to their timber value as well as contribution to wildlife habitat, climatic balance and stronghold on water releases. The supra-annual mass flowering of dipterocarps occurs in irregular intervals of two to ten years, possibly synchronously across Asia. Predicting the likelihood of their regeneration, to subsequently make plans regarding species for reforestation, can be aided by providing access to a knowledge base of dipterocarps, including information on the fac

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Han, Chaeyeon, and Yongjune Lee. "Text Mining Utilization on the Perception of Organizational Core Talent Competencies among Employees: A Preliminary Survey for Core Competency Education and Development." Korean Career, Entrepreneurship & Business Association 8, no. 2 (2024): 99–117. http://dx.doi.org/10.48206/kceba.2024.8.2.99.

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The purpose of this study is to investigate and analyze the competencies of organizational core talents as perceived by employees. To achieve this, interviews and survey questions were created through a review of prior research, using both structured and unstructured questions. Subsequently, data from 134 employees, excluding insincere respondents, were collected through offline interviews and online surveys. The analysis utilized text mining techniques, a big data analysis method, and was conducted by converting descriptive response content into text files using R 4.3.2. The research methodol

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