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  • Course Information
    • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Data Mining BBY412 FALL-SPRING 2+0 E 5
    Learning Outcomes
    1-Learns data processing, classification, clustering, and analysis with data mining techniques.
    2-To be informed about data warehouses
    3-Compares data and text mining.
  • ECTS / WORKLOAD
    • ActivityPercentage

    (100)

    		NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14228
    Classroom study (Pre-study, practice)000
    Assignments1012424
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)4013030
    Project0000
    Laboratory 0000
    Final exam (exam + preparation) 5016060
    0000
    Total Workload (hours)   142
    Total Workload (hours) / 30 (s)     4,73 ---- (5)
    ECTS Credit   5
  • Course Content
    • Week Topics Study Metarials
    1 Introduction to Data Mining SR-3
    2 Data Mining Process R1- CHAPTER 3
    3 Data understanding R1- CHAPTER 3
    4 Data Preparation R1- CHAPTER 4
    5 Data cleaning R1- CHAPTER 4
    6 Eliminating missing data R1- CHAPTER 4
    7 Data Transformation - Reduction R1- CHAPTER 4
    8 Factor Analysis R1- CHAPTER 4
    9 Distance and Similarity R1- CHAPTER 5
    10 Classification R1- CHAPTER 6
    11 Clustering R1- CHAPTER 7
    12 Text Mining SR2- CHAPTER 1
    13 Text Mining SR2- CHAPTER 1
    14 Data and Text Mining Applications
    Prerequisites -
    Language of Instruction Turkish
    Responsible Assoc. Dr. Kasım BİNİCİ
    Instructors -
    Assistants -
    Resources K1-Akpınar, H. (2014). Data: Veri Madenciliği Veri Analizi. Papatya. Akpınar, H. (2014). Data: Veri Madenciliği Veri Analizi. Papatya.
    Supplementary Book SR1. Binici, K. (2018). Kütüphane ve Bilgi Biliminde Tema ve Yönelim. İstanbul: Hiperyayın.
    SR2. Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C. ve Wirth, R. (2000). CRISP-DM 1.0 Step-by-step data mining guide. SPSS. https://the-modeling-agency.com/crisp-dm.pdf adresinden erişildi.
    SR3. Gürsakal, N. (2014). Büyük Veri. Bursa: Dora.
    SR4. Miner, G., Delen, D., Elder, J., Fast, A., Hill, T. ve Nisbet, R. A. (2012). Practical text mining and statistical analysis for non-structured text data applications. Waltham, MA: Academic Press.
    SR5. North, M. (2012). Data mining for the masses. http://rapidminer.com/wp-content/uploads/2013/10/DataMiningForTheMasses.pdf adresinden erişildi.
    SR6. Pektaş, A. O. (2013). SPSS ile Veri Madenciliği. Dikeyeksen.
    SR7. Şeker, Ş. E. (2013). İş Zekası ve Veri Madenciliği. Cinius.
    Goals To introduce the data mining techniques and give information about applications that processed on data structures
    Content In this course, data mining process, appropriate software in data mining, data mining models, sample research models and applications will be discussed.
  • Program Learning Outcomes
    • Program Learning Outcomes Level of Contribution
    1 Recognizing and comprehending the terms and concepts (Turkish and foreign) regarding information and records management -
    2 Provision of sensitivity training for social, economic and cultural changes with ability of making analysis in terms of professional perspective. 1
    3 To be aware of problems regarding discipline through assessment, and critical thinking and finally, create solutions. -
    4 Improving the ability and capacity of systematic thinking. 4
    5 Developing an interdisciplinary perspective and evaluation. 3
    6 Establishing programs leads to information awareness in the society meeting following requirements: enable individuals describe their needs of information and improve ability to find out and evaluate information for themselves. -
    7 Building foundations that is required for information retrieval selectively and comprehend related techniques and methods -
    8 Evaluating information retrieval process in national and international information systems -
    9 Recognizing a variety of information sources (general and special) regarding all subject areas according to types and contents -
    10 Gaining the ability to read and evaluate records and sources in Ottoman language -
    11 Communicating with reel and potential users -
    12 Foundations of conceptual knowledge of services with respect to types of information centers and their users -
    13 Gaining the ability to use techniques required for organization of information -
    14 Recognizing products, systems and models related with information and communication technologies and enhancing use of them. 4
    15 Gaining the ability to measure the quality of digital knowledge by various disciplines and evaluate information services. 4
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