USING THE TECHNIQUES OF DATA MINING AND TEXT MINING IN EDUCATIONAL RESEARCH

Today it is possible to store and retrieve official and personal data; everyone can store photographs, movies and notes in electronic settings. The amount of such data increases everyday (some call it “information boom”). Many search engines can scan electronic data based on key terms (or based on content); some sales companies also use such data to offer “best” sales. Some computer programs provide their clients with textual data collected from Internet sources. Such programs are mostly used by sales companies. Today emails, notes on facebook and twitter as well as blogs are checked for security purposes. In science information-based search engines such as GoPubMed are employed. In short, computer-assisted text analysis has been used in different fields and various techniques make it possible to analyse data.

Anahtar Kelimeler:

TEXT MINING

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Akpınar, H., (2000), Veri Tabanlarında Bilgi Keşfi ve Veri Madenciliği. İ.Ü. İşletme Fakültesi Dergisi, 29(1), 1-22. Arslan, A.A. (2011), Türkçe Metinlerden Anlamsal Bilgi Çıkarımı İçin Bir Veri Madenciliği Uygulaması, Başkent Üniversitesi Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi (http://angora.baskent.edu.tr/acik_arsiv/dosya_oku.php?psn=2409&yn=352&dn=1) Aydın, C.R., Erkan, A., Güngör, T. & Takçı, H., (2013). Sözlük Tabanlı Kavram Madenciliği: Türkçe için bir Uygulama, 30. Ulusal Bilişim Kurultayı, November 2013, Ankara. http://www.cmpe.boun.edu.tr/~gungort/papers/Sozluk%20Tabanli%20Kavram%20Madenciligi%20-%20Turkce%20icin%20bir%20Uygulama.pdf Bilgin, T.T. ve Çamurcu, A.Y., (2008), Çok Boyutlu Veri Görselleştirme Teknikleri, Akademik Bilişim 2008, 30 Ocak - 01 Şubat. Çanakkale Onsekiz Mart Üniversitesi, Çanakkale, 107-112. http://ab.org.tr/ab08/kitap/Bildiriler/Bilgin_Camurcu_AB08.pdf Blei, D., Ng, A. & Jordan, M. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3:993–1022. https://www.cs.princeton.edu/~blei/papers/BleiNgJordan2003.pdf Cobo, M.J., López-Herrera, A.G., Herrera-Viedma, E. & Herrera, F. (2011). Science Mapping Software Tools: Review, Analysis, and Cooperative Study Among Tools, Journal of the American Society for Information Science and Technology, 62(7). 1382–1402, https://www.researchgate.net/publication/227733641_Science_Mapping_Software_Tools_Review_Analysis_and_Cooperative_Study_Among_Tools Cohen, K.B. & Hunter, L. (2008), Getting Started in Text Mining, PLoS Comput Biol. 4(1): e20. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2217579/ Çalış, K., Gazdağı, O. & Yıldız, O. (2013), Reklam İçerikli Epostaların Metin Madenciliği Yöntemleri ile Otomatik Tespiti, Bilişim Teknolojileri Dergisi, 6(1), 1-7. http://www.btd.gazi.edu.tr/article/viewFile/1041000157/pdf De Bellis, N.(2009). Bibliometrics and citation analysis: from the Science citation index to cybermetrics. Scarecrow Press. Dolgun, M.Ö.,Özdemir, T.G. & Oğuz, D. (2009), Veri madenciliğinde yapısal olmayan verinin analizi: Metin ve web madenciliği, İstatistikçiler Dergisi, 2, 48-58. http://dergipark.ulakbim.gov.tr/jssa/article/download/5000047710/5000045038 Donath, J., 2002, A semantic approach to visualizing online conversations, Communications of the ACM, 45(4). 45-49. DOI:10.1145/505248.505271 Friendly, M. (2006). A Brief History of Data Visualization, C. Chen, W. Hardle & A. Unwin (Eds), Handbook of Computational Statistics: Data Visualization. Springer. 1-43. http://www.datavis.ca/papers/hbook.pdf He, Q. (1999). Knowledge Discovery Through Co-Word Analysis, Library Trends, 48(1). 133-159. https://www.ideals.illinois.edu/bitstream/handle/2142/8267/librarytrendsv48i1i_opt.pdf?sequ Hearst, M. (2009), What is text mining, http://www.sims.berkeley.edu/~hearst/textmining.html Hearst, M.A. & Rosner, D., (2008). Tag Clouds: Data Analysis Tool or Social Signaller?, Hawaii International Conference on System Sciences, Proceedings of the 41st Annual, 7-10 Ocak 2008, 160-160. DOI: 10.1109/HICSS.2008.422 Hearst, M.A. (2008). What’s Up With Tag Clouds, Visual Business Intelligence Newsletter, Mayıs. 1-5. https://www.perceptualedge.com/articles/guests/whats_up_with_tag_clouds.pdf Hsieh, H.-F. & Shannon, S.E. (2005), Three Approaches to Qualitative Content Analysis, Qualitative Health Research, 15(9), 1277-1288. DOI: 10.1177/1049732305276687 Puri, S. (2011). A Fuzzy Similarity Based Concept Mining Model for Text Classification. Text Document Categorization Based on Fuzzy Similarity Analyzer and Support Vector Machine Classifier, International Journal of Advanced Computer Science and Applications (IJACSA), 2(11), 115-121. https://arxiv.org/ftp/arxiv/papers/1204/1204.2061.pdf Savaş, S., Topaloğlu, N. & Yılmaz, M. (2012). Veri Madenciliği Ve Türkiye’deki Uygulama Örnekleri, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 11(21). 1-23. http://www.ticaret.edu.tr/uploads/yayin/fen21_dosyalar/1-23.pdf Savaşan, S. & Diri, B. (2011). Automatic Tag Cloud Generation From Turkish Contents, Mühendislik ve Fen Bilimleri Dergisi Sigma 29, 156-169. http://eds.yildiz.edu.tr/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=1867 Shi, C., Verhagen, M. & Pustejovsky, J. (2014). A Conceptual Framework of Online Natural Language Processing Pipeline Application, Proceedings of the Workshop on Open Infrastructures and Analysis Frameworks for HLT, Dublin, Ireland. 53–59. http://www.aclweb.org/anthology/W14-5206 Şentürk, A. (2006). Veri Madenciliği: Kavram ve Teknikler, 2. Bursa: Ekin Yay. Tan, A.H., Yu, P.S. (2004), Guest Editorial: Text and Web Mining, Applied Intelligence 18, 239-241. Wang, L., Wang, G. & Alexander, C.A. (2015). Big Data and Visualization: Methods, Challenges and Technology Progress, Digital Technologies, 1(1), 33-38. http://pubs.sciepub.com/dt/1/1/7/