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Journal articles on the topic 'Textmining'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 February 2023

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1

Han, Haneul, Yongjin Kim, and Nala Shin. "Textmining Analysis on Block Chain and Logistics Industry." Journal of Humanities and Social sciences 21 12, no. 5 (October 31, 2021): 2567–78. http://dx.doi.org/10.22143/hss21.12.5.181.

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Schönbach, Christian, Takeshi Nagashima, and Akihiko Konagaya. "Textmining in support of knowledge discovery for vaccine development." Methods 34, no. 4 (December 2004): 488–95. http://dx.doi.org/10.1016/j.ymeth.2004.06.009.

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Kim, J. D., T. Ohta, Y. Tateisi, and J. Tsujii. "GENIA corpus--a semantically annotated corpus for bio-textmining." Bioinformatics 19, Suppl 1 (July 3, 2003): i180—i182. http://dx.doi.org/10.1093/bioinformatics/btg1023.

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Go, Gwang-Su, Won-Kyo Jung, Young-Geun Shin, Sang-Sung Park, and Dong-Sik Jang. "A Study on Development of Patent Information Retrieval Using Textmining." Journal of the Korea Academia-Industrial cooperation Society 12, no. 8 (August 31, 2011): 3677–88. http://dx.doi.org/10.5762/kais.2011.12.8.3677.

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KODAIRA, Tomoe, and Takehiko ITO. "A textmining study of titles of autobibliography of people with schizophrenia." Proceedings of the Annual Convention of the Japanese Psychological Association 77 (September 19, 2013): 1PM—108–1PM—108. http://dx.doi.org/10.4992/pacjpa.77.0_1pm-108.

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Yang, Ji yoon and Joo Yun Kim. "A study on public perception of wales Millenium Centre architecture using textmining." Journal of Korea Intitute of Spatial Design 12, no. 5 (October 2017): 193–201. http://dx.doi.org/10.35216/kisd.2017.12.5.193.

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Yang, Ji-Yun. "A Study on Public Perception on Department Store Experience Trend through Textmining." Journal of the Korean Institute of Interior Design 31, no. 4 (August 31, 2022): 41–49. http://dx.doi.org/10.14774/jkiid.2022.31.4.041.

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Park, Jinkyeun, Taekyoun Kim, and Min Song. "Entitymetrics Analysis of the Research Works of Dong-ju Yun using Textmining." Journal of the Korean BIBLIA Society for library and Information Science 28, no. 1 (March 30, 2017): 191–207. http://dx.doi.org/10.14699/kbiblia.2017.28.1.191.

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Yang, Ji Yun. "A Study on Iconic Architecture Strategy through SNS Textmining - focused on British cases -." Journal of Basic Design & Art 23, no. 3 (June 30, 2022): 153–64. http://dx.doi.org/10.47294/ksbda.23.3.12.

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Oh, Chang-Seok, Yong-taeck Lee, and Minsu Ko. "Establishment of ITS Policy Issues Investigation Method in the Road Section applied Textmining." Journal of The Korea Institute of Intelligent Transport Systems 15, no. 6 (December 31, 2016): 10–23. http://dx.doi.org/10.12815/kits.2016.15.6.010.

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Oliveira Lima Junior, Paulo, Luiz Gonzaga de Castro Junior, and Andre Luiz Zambalde. "Applying Textmining to Classify News About Supply and Demand in the Coffee Market." IEEE Latin America Transactions 14, no. 12 (December 2016): 4768–74. http://dx.doi.org/10.1109/tla.2016.7817009.

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Thanh, Nguyen Chi, Koichi Yamada, and Muneyuki Unehara. "A Similarity Rough Set Model for Document Representation and Document Clustering." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 2 (March 20, 2011): 125–33. http://dx.doi.org/10.20965/jaciii.2011.p0125.

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Document clustering is a textmining technique for unsupervised document organization. It helps the users browse and navigate large sets of documents. Ho et al. proposed a Tolerance Rough Set Model (TRSM) [1] for improving the vector space model that represents documents by vectors of terms and applied it to document clustering. In this paper we analyze their model to propose a new model for efficient clustering of documents. We introduce Similarity Rough Set Model (SRSM) as another model for presenting documents in document clustering. The model is evaluated by experiments on test collections. The experiment results show that the SRSM document clusteringmethod outperforms the one with TRSM and the results of SRSM are less affected by the value of parameter than TRSM.

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Delespierre, Tiba, and Loic Josseran. "Issues in Building a Nursing Home Syndromic Surveillance System with Textmining: Longitudinal Observational Study." JMIR Public Health and Surveillance 4, no. 4 (December 13, 2018): e69. http://dx.doi.org/10.2196/publichealth.9022.

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Боярский, Кирилл Кириллович, Евгений Александрович Каневский, and Дарья Андреевна Буторина. "К вопросу о разрешении семантической омонимии топонимов в русскоязычных текстах." Компьютерная лингвистика и вычислительные онтологии, no. 3 (December 30, 2019): 19–28. http://dx.doi.org/10.17586/2541-9781-2019-3-19-28.

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Одним из способов анализа документов на естественном языке является извлечение именованных сущностей, в частности, топонимов. Особенность данной задачи заключается в необходимости разрешать омонимию топонимов с другими словами языка. Областью исследования являются русскоязычные тексты, имеющие общеполитический, художественный и узкоспециальный характер. В качестве инструмента семантико-синтаксического анализа использовался парсер SemSin . Для снятия омонимии топонимов проводился поиск сопутствующих слов двух типов: определяющих, называющих классы географических объектов (река, город), и маркерных, образующих достаточно частотные словосочетаниями с топонимами (излучина, предместье). Составлены «микрословари» маркерных слов для топонимов классов рек, городов и гор. Показано, что их использование в ряде случаев позволяет однозначно определить, что данное слово является топонимом соответствующего класса, в том числе для слов, отсутствующих в словаре. Полученные результаты не зависят от конкретного парсера и словаря и могут быть использованы для повышения точности технологий TextMining .

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Westphal, Andrea, and Olaf Zawacki-Richter. "Von der Allgemeinen Erziehungswissenschaft zur Empirischen Bildungsforschung?" Zeitschrift für Erziehungswissenschaft 24, no. 3 (March 30, 2021): 641–69. http://dx.doi.org/10.1007/s11618-021-01008-5.

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ZusammenfassungDer vorliegende Beitrag beschäftigt sich mit den Publikationen, die in der Zeitschrift für Erziehungswissenschaft (ZfE) in den Jahren 1998–2017 veröffentlicht wurden. Angesichts der Veränderungen in der erziehungswissenschaftlichen Forschungslandschaft in der jüngeren Vergangenheit untersuchen wir, inwiefern sich eine veränderte Schwerpunktsetzung auch in den Beiträgen der ZfE nachweisen lassen. Dazu führen wir zunächst eine quantitative Textanalyse durch und identifizieren die häufigsten sowie die charakteristischen Bigramme (Zweiwortsequenzen) in vier aufeinanderfolgenden Fünfjahres-Abschnitten (1998–2002, 2003–2007, 2008–2012, 2013–2017). Zudem prüfen wir, inwiefern bestimmte Wortstämme (bspw. „erziehungswissenschaft“, „bildungsforsch“, „didakt“) über die Jahre hinweg häufiger auftreten. Schließlich erstellen wir mit dem Textmining Tool Leximancer™ concept maps, die Hinweise auf die semantische Struktur der Themengebiete und Schlüsselkonzepte geben. Die Ergebnisse deuten darauf hin, dass im gesamten Zeitraum mehrheitlich Beiträge mit empirischem Fokus publiziert wurden, ein inhaltlicher Fokus auf sozialen Aspekten von Bildung lag und die Beschäftigung mit der allgemeinen Erziehungswissenschaft abnahm.

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Yoo, Ji-Yeon, and Min-Jung Chang. "Analysis of Domestic and International Reactions to Modern Hanbok in Korean Wave : Use of Textmining Methods." Journal of Korean Traditional Costume 24, no. 3 (September 30, 2021): 179–97. http://dx.doi.org/10.16885/jktc.2021.09.24.3.179.

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Wei, Zhenfeng, and Xiaohua Zhang. "A Filtering Algorithm of Main Word Frequency for Online Commodity Subject Classification in E-Commerce." International Journal of Circuits, Systems and Signal Processing 15 (March 30, 2021): 218–24. http://dx.doi.org/10.46300/9106.2021.15.25.

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—Based on the traditional classification of plain text in E-Commerce, this article has put forward a processing method in accordance with semi-structured data and main information in web pages, which enhances the accuracy of the product distribution. On the basis of the traditional textmining, combined with the structure and links of web page, this article has proposed an improved web page text representation model in E-Commerce based on supporting vector machines and web text classification algorithm, but there are still a lot of shortcomings waiting for further improvement. According to the data contrast in precision ratio, recall ratio and F-measure, the effect of the improved experiment with LDF-IDF is comprehensively better than that of tf-idf. The precision rate in certain classification can reach 100%, but there is low precision rate caused by items with fewer samples or samples fuzziness. Therefore, the classification of the correct category will directly affect the effect of classification.

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Karpen, Ingo, and Carolin Plewa. "From Muso to Academic and Back: A Time and Person-Based Acknowledgement of Michael Kleinaltenkamp." Journal of Service Management Research 4, no. 2-3 (2020): 75–83. http://dx.doi.org/10.15358/2511-8676-2020-2-3-75.

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The year 2020 sees an important milestone for Professor Michael Kleinaltenkamp (Michael hereafter), as he concludes his official academic working life. This paper acknowledges the significant contribution Michael has made over the years. In particular, using Leximancer to undertake textmining of Michael’s English language publications, we not only uncover the underlying structure of these contributions but also explore if and how focal themes of his research have changed, particularly considering his close engagement with the Australasian academic marketing community. Findings indicate foundational facets and the overall gestalt of his research over time, yet also point to important differences across the time periods analysed. Finally, we reflect on our findings from a musical perspective, drawing on Michael’s passion for music, as we thank him for the many jams and the rehearsing, aswell as for his support for the bands and scenes he belongs to. For future research, it should be noted that future acknowledgements would benefit from cooking as a metaphor to complete the picture.

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TSUDA, Kohei, Ruck THAWONMAS, and Yuki KONNO. "Discovering Keywords by Measuring Influence Rates in Bulletin Board Services : An Application of Textmining to Online Games." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 17, no. 2 (2005): 184–93. http://dx.doi.org/10.3156/jsoft.17.184.

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Joe, Yong Lim. "A Study on the Inaugural Address of the President of Korea: Focusing on feature values in Textmining." Liberal Arts Innovation Center 9 (May 30, 2022): 351–79. http://dx.doi.org/10.54698/kl.2022.9.351.

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Unlike artificial languages, natural languages are difficult for computers to process directly. Therefore, it is necessary to process it as structured data. In the end, by giving weight to the sample text, the frequency of appearance in the document was weighted. The inaugural address data was entered through information filtering of text mining, and it was possible to obtain the result of the characteristic value according to the relation to the main word. This study analyzed the vocabulary of the inaugural speeches of past presidents of the Republic of Korea. After refining words through morpheme analysis, we found vocabulary frequency and characteristic values, and the data was visualized in wordcloud. This study did not perform a fragmentary analysis of the existing lexical analysis. This study presented feature values and word clouds. Therefore, it was possible to extract objective keywords representing the characteristics of the keywords.

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Yoon, Seungjin, Suhwan Kim, and Kyungshik Shin. "Development of the Accident Prediction Model for Enlisted Men through an Integrated Approach to Datamining and Textmining." Journal of Intelligence and Information Systems 21, no. 3 (September 30, 2015): 1–17. http://dx.doi.org/10.13088/jiis.2015.21.3.01.

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Kodaira, Tomoe, and Takehiko Ito. "A textmining study of narrative of recovery by people with mental disorders at tohjisha-kenkyu in Urakawa Bethel House." Proceedings of the Annual Convention of the Japanese Psychological Association 78 (September 10, 2014): 1AM—1–045–1AM—1–045. http://dx.doi.org/10.4992/pacjpa.78.0_1am-1-045.

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23

Hernandez, Andres, Harry Hochheiser, John Horn, Rebecca Crowley, and Richard Boyce. "Testing Pre-Annotation to Help Non-Experts Identify Drug-Drug Interactions Mentioned in Drug Product Labeling." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (October 14, 2014): 14–15. http://dx.doi.org/10.1609/hcomp.v2i1.13213.

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In this study, a system for allowing combination of textmining and crowdsourcing of annotation approaches for detection of DDIs from drug package inserts is presented. An annotation study was designed to evaluate expert versus non-expert curation performance, and the impact of NLP pre-annotation on precision and recall on both groups. The design and development of the system and annotation study, consisted of three stages. First, our existing NLP pipeline for DDI extraction was improved, and it was used to preannotate 208 drug product labels with drug mentions and DDIs. Secondly, a DDI machine readable representation scheme was created using the Annotation Ontolgy. This model allowed us to load the NLP preannotated drug label sections into our plugin for human curation created using the Annotation tool DOMEO. Finally, the annotation study was performed along with usability questionnaires for collecting qualitative feedback. To our knowledge, this is the first study in comparing experts and non-experts for pharmacokinetic DDI annotation. Results showed lower performance on non-experts compared with expert annotation without the use of NLP,and an improvement of non-expert annotation performance using the NER module of the NLP assistance. Simplification of the workflow for NLP assisted annotation is necessary for scaling ourapproach.

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Rafi, Muhammad, Muhammad Waqar, Hareem Ajaz, Umar Ayub, and Muhammad Danish. "Document Clustering using Self-Organizing Maps." MENDEL 23, no. 1 (June 1, 2017): 111–18. http://dx.doi.org/10.13164/mendel.2017.1.111.

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Cluster analysis of textual documents is a common technique for better ltering, navigation, under-standing and comprehension of the large document collection. Document clustering is an autonomous methodthat separate out large heterogeneous document collection into smaller more homogeneous sub-collections calledclusters. Self-organizing maps (SOM) is a type of arti cial neural network (ANN) that can be used to performautonomous self-organization of high dimension feature space into low-dimensional projections called maps. Itis considered a good method to perform clustering as both requires unsupervised processing. In this paper, weproposed a SOM using multi-layer, multi-feature to cluster documents. The paper implements a SOM usingfour layers containing lexical terms, phrases and sequences in bottom layers respectively and combining all atthe top layers. The documents are processed to extract these features to feed the SOM. The internal weightsand interconnections between these layers features(neurons) automatically settle through iterations with a smalllearning rate to discover the actual clusters. We have performed extensive set of experiments on standard textmining datasets like: NEWS20, Reuters and WebKB with evaluation measures F-Measure and Purity. Theevaluation gives encouraging results and outperforms some of the existing approaches. We conclude that SOMwith multi-features (lexical terms, phrases and sequences) and multi-layers can be very e ective in producinghigh quality clusters on large document collections.

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Javed, Ambreen, Hassan Burair Abbas, Saad Ahmed, Aashi Ahmed, and Gulshan Ara Trali. "In Silico Analysis of Molecular Interactions of FZD10 in Wnt Signaling Pathway Involved in Wound Healing." Pakistan Journal of Medical and Health Sciences 15, no. 10 (October 30, 2021): 2841–44. http://dx.doi.org/10.53350/pjmhs2115102841.

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Background: Wnt signaling pathway is a complex network involving important molecular and functional interaction molecules. It has a key role in the wound healing process. Aim: To identify the molecular interactions of FZD10 in Wnt signalling pathway in wound healing. Study Design: Computation based in silico study Place and Duration of Study: Department of Biochemistry, Swat Medical College (STMC), Saidu Shareef, Swat, Pakistan from 1st March 2021 to 31st August 2021. Methodology: We applied Search Tool for the Retrieval of Interacting Gene/Proteins (STRING) analysis, using specific parameters including (1) Textmining (2) Experiments (3) Databases (4) Co-expression (5) Neighbourhood (6) Gene fusion and (7) Co-occurrence for the identification of molecular interactions of the Wnt signaling pathway. The maximum number of interactors was set at 20 and highest confidence level at 0.900. Results: STRING network analysis revealed that Frizzled Homologue 10 (FZD10) protein interacts with Hypoxia- Inducible Lipid Droplet-Associated Protein(HILPDA), Wnt1,Wnt3A, Wnt5A,Wnt7A,Wnt7B, Wnt16, Low-density lipoprotein receptor-related protein 5 (LRP5), LRP6, and Dishevelled Segment Polarity Protein 1 (DVL1) proteins in Wnt signaling pathway and contributes in various cellular activities, including cell proliferation, cellular migration, differentiation, apoptosis and stem cell regeneration, which are crucial for the wound healing process. Conclusion: Functional enrichment analysis revealed that FZD10 protein is a key player in Wnt signaling pathway and has the potential to be considered as a candidate molecule for the therapeutics of wound healing process in future. Keywords: Wnt Signaling pathway, STRING, molecular interactions, Frizzled-10, Cell proliferation, Cell migration

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Sakharova, Svetlana Mihailovna, Tatiana Alexandrovna Golovina, Irina Leonidovna Avdeeva, and Larisa Vladimirovna Parakhina. "Strategic management of the Arctic zone development based on the multicentric approach." Mezhdunarodnaja jekonomika (The World Economics), no. 4 (March 23, 2022): 285–98. http://dx.doi.org/10.33920/vne-04-2204-02.

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The relevance of the research is determined by the need to create scientifically substantiated approaches to the strategic development management of the Arctic zone on the basis of a multicentric approach. The state management of the development of this region on the basis of the multicentric approach will contribute to the economic growth of the territory. The aim of the research is to study the concept of multicentric interaction between internal and external actors in the territory of the Arctic region, the specifics of their implemented strategic activities, to assess their impact on the state policy of Russia in the Arctic zone in order to develop measures aimed at transforming the strategic development of this territory in order to develop the Arctic zone potential as part of a unified nationwide agenda. The author’s proposed concept of strategic management of the Arctic region development involves the formation of human and social capital, support of local initiatives, diversification of activities, development of public policy based on a balanced consideration of the interests of internal and external actors, as well as the development of appropriate mechanisms to improve the efficiency of the entire Arctic ecosystem. The article uses the methods of structural and system analysis to study the essence of the stakeholder approach in the management of socio-economic systems. The retrospective assessment and textmining of domestic and foreign experience of studying the stakeholder management system allowed to define its role in the state management of socio-economic development of the Arctic zone and to propose the concept of multicentric approach, which allows to differentiate the interests of parties and choose the most effective interaction strategy. It is concluded that to improve the effectiveness of state management of socio-economic development of the Arctic zone it is necessary to develop strategic measures to involve stakeholders in management decision-making processes.

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Lee, Jihyun, Kwang Min Cho, and Hyungchul Joo. "This research aims to examine how bicycle race is perceived in our society through a Big Data-based text-mining analysis. Data were collected from the major internet portal sites such as Naver and Daum by using Textom, an data analysis tool, and only those published during the period from June 16th, 2018 to June 16th, 2020 were collected. Textmining was applied to the collected data and then they were visually analyzed through a CONCOR analysis. Throughout these processes, the following findings were discovered. First, the ten words highly ranked in the keyword analysis result were COVID-19, KCYCLE·KBOAT Fund Rasing Office, stadium closure, bicycle racer, bicycle, extension, frame, recommendation, spread, and Korea Sports Promotion Foundation. The eight major groups produced by the CONCOR analysis includes ‘direction of bicycle race management’, ‘bicycle race trading’, ‘solution for speculative betting’, ‘award-winning career issue’, ‘racer branding’, ‘consideration for bicycle race products’, ‘trade of bicycle race products’ and ‘means for online promotion’. The word most often mentioned with the keyword ‘bicycle race’ is COVID-19, which has emerged as the biggest social issue during this period, For the past two years. On the other hand, the words relevant to betting have often been mentioned as those in the ‘bicycle race trading’ group, indicating that, for the participants in the bicycle race, betting information has one of the most important concerns. Meanwhile, ‘award-winning career issue’ and ‘racer branding’ are two groups, from which the public interests in the information of bicycle racers, especially their award-winning career, could be inferred. The groups such as ‘consideration for bicycle race products’ and ‘trade of bicycle race products’ suggest that bicycle racing has become a significant part of public sports. At the same time, the negative public perception of bicycle race is also identified from the group of ‘solution for speculative betting’ but the keyword of the ‘means for online promotion’ group is expected to be useful for future marketing to bring out positive effects." Korean Journal of Physical Education 59, no. 5 (September 30, 2020): 103–16. http://dx.doi.org/10.23949/kjpe.2020.9.59.5.8.

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Chayan, Chakrabarti, Luger George, Laird Angela, and Turner Jessica. "Textmining for cognitive paradigm annotation." Frontiers in Neuroinformatics 7 (2013). http://dx.doi.org/10.3389/conf.fninf.2013.08.00013.

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"Exploring pharmacological principle of Artemisia carvifolia with textmining technology." China Journal of Chinese Materia Medica, August 15, 2016. http://dx.doi.org/10.4268/cjcmm20161622.

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Schmidt, Hans-Günter. "Kallimachos: Digital Humanities als Auftrag der Universitätsbibliothek Würzburg." ABI Technik 36, no. 3 (January 1, 2016). http://dx.doi.org/10.1515/abitech-2016-0035.

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Zusammenfassung:KALLIMACHOS baut an der Universitätsbibliothek Würzburg ein Digital-Humanitites-Zentrum mit den Arbeitsschwerpunkten OCR, digitale Edition, Textmining und quantitative Analyse auf. Das Zentrum bietet eine technische und soziale Infrastruktur, die Geisteswissenschaftler bei der Beantwortung von Forschungsfragen unterstützt und innovative Werkzeuge, Methoden, prototypische Arbeitsabläufe und Dienste entwickelt. In sechs Beispielprojekten aus Papyrologie, Geschichte, Philologie, Philosophie und Pädagogik werden die Neuentwicklungen erprobt, die Fruchtbarkeit der neuen Verfahren vermittelt und Bausteine für ein künftiges Forschungsdatenmanagement geschaffen. Das BMBF unterstützt den Aufbau des Zentrums bis Ende 2017 im Rahmen der Förderlinie „eHumanities“.

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"Word Representation for Biomedical Textmining based on NNGM with Image to Text Conversion." International Journal of Science and Research (IJSR) 5, no. 5 (May 5, 2016): 2325–29. http://dx.doi.org/10.21275/v5i5.nov163999.

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Stamm, Isabell, Lena Schürmann, Katharina Scheidgen, Stefan Berwing, and Arne Maibaum. "Marktabhängigkeit und ihre Bedeutung für die Grenzziehungen von Solidarität." Zeitschrift für Soziologie, October 20, 2022. http://dx.doi.org/10.1515/zfsoz-2022-0019.

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Zusammenfassung Der Beitrag untersucht Grenzlinien der Solidarität. Er betrachtet, wie in Krisensituationen Unterstützungsbedarfe für jene soziale Gruppen verhandelt werden, die in etablierten Solidaritätsdiskursen in eine Deutungslücke fallen. Untersuchungsgegenstand bildet die öffentliche Verhandlung von Solidarität mit Soloselbstständigen zu Beginn der Coronapandemie. Gestützt auf Auswertungen von 21 qualitativen Interviews und ein Textkorpus mit 2428 Zeitungsartikeln zeichnen wir den Diskurs um Soforthilfe nach. Mittels einer Kombination aus strukturierender Inhaltsanalyse und Textmining zeigen wir auf, dass die Deutungsfigur der Marktabhängigkeit von Soloselbstständigen in dieser Krisenzeit dazu dient, die Hilfsbedürftigkeit der Gruppe zu identifizieren (soziale Grenzziehung), aber auch die Ausgestaltung der Hilfe kontrovers zu diskutieren (substanzielle Grenzziehung). Wir zeigen, wie sich Solidaritätsnormen im Diskursverlauf konfigurieren und dabei Marktabhängigkeit als relevante Grenze für Solidarität freigeben, diese aber nur zeitlich begrenzt wirksam bleibt.

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Kaarakainen, Suvi-Sadetta, and Meri-Tuulia Kaarakainen. "Tulevaisuuden kansalaisia rakentamassa." AFinLAn vuosikirja, November 2, 2018, 22–40. http://dx.doi.org/10.30661/afinlavk.69269.

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The concept of new literacies refers to new forms of literacy. The meaning of literacy is constantly changing as new technologies and new social practices emerge. To be literate in the future means being able to use a combination of new technologies and new social practices that have not yet appeared. This has important implications for education. In this paper, we analyse Finnish educational policy and strategy papers from 1998 to 2014 conducting textmining and traditional close reading. By means of lexical dispersion we separate three distinct time periods: before 2005, the years 2005–2010 and after 2010. By close reading and topic modeling, we examine the emergence of new literacies in our research material and how thisis related to the sociocultural contexts of each period of time.

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Darmawan, Agus, and Syamsiah Syamsiah. "Analisa Model Support Vector Machine Textmining pada Komentar Positif dan Negatif untuk Review PerbandinganWhatsapp Vs BBM." STRING (Satuan Tulisan Riset dan Inovasi Teknologi) 1, no. 1 (August 27, 2016). http://dx.doi.org/10.30998/string.v1i1.971.

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Mohammadi, Navid, Nader Seyyedamiri, and Saeed Heshmati. "Text data-driven new product development: a systematic mapping review." Nankai Business Review International, November 17, 2022. http://dx.doi.org/10.1108/nbri-04-2021-0029.

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Purpose The purpose of this study/paper is conducting a Systematic mapping review, as a systematic literature review method for reviewing the literature of new product development by textmining and mapping the results of this review. Design/methodology/approach This research has been conducted with the aim of systematically reviewing the literature on the field of design and development of products based on textual data. This research wants to know, how text data and text mining methods, can use for the design and development of new products. Findings This review finds out what are the most popular algorithms in this field? What are the most popular areas in using these approaches? What types of data are used in this area? What software is used in this regard? And what are the research gaps in this area? Originality/value The contribution of this review is creating a macro and comprehensive map for research in this field of study from various aspects and identifying the pros and cons of this field of study by systematic mapping review.

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"Soft Computing Techniques for Weather Change Predictions in Delhi." International Journal of Recent Technology and Engineering 8, no. 4 (November 30, 2019): 793–800. http://dx.doi.org/10.35940/ijrte.d7382.118419.

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Weather forecasting and warning is the application of science and technology to predict the state of the weather for a future time of a given location. The emergence of adverse effects of weather has endangered the life of general public in previous years. The unpredicted flood and super cyclone in many places have created havoc. The government and private agencies are working on its behaviours but still it is challenging and incomplete. But, the application of soft computing techniques in weather prediction has made a significant perfomance now a days. This research work presents the comparative study of soft computing techniques like MultiLayer Perceptron(MLP), Support Vector Machine(SVM) and J48 Decision Tree for forecasting the weather of Delhi with ten years data comprising of temperature, dew, humidity, air pressure, wind speed and visibility. This paper tries to describe the comparison among above models using four different error values like Relative Absolute Error(RAE), Mean Absolute Error(MAE), Root Mean Squared Error(RMSE) and Root Relative Squared Error(R2 ) with a proposed model by defining new algorithm. Further the performance can be enhanced if textmining will be applied in this proposed model.

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Shimazaki, Kei-ichi, Kei-ichi Shimazaki, Tatsuya Kushida, Koji Yamauchi, and Toshihisa Takagi. "Apply of Textmining Method to Study the Roles in Improving the Health by Lactoferrin, a Multi-Functional Milk Protein." Nature Precedings, October 25, 2010. http://dx.doi.org/10.1038/npre.2010.5100.

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Shimazaki, Kei-ichi, Tatsuya Kushida, Koji Yamauchi, and Toshihisa Takagi. "Apply of Textmining Method to Study the Roles in Improving the Health by Lactoferrin, a Multi-Functional Milk Protein." Nature Precedings, October 25, 2010. http://dx.doi.org/10.1038/npre.2010.5100.1.

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