732 A 75 Advanced Data Mining TDDD 41

732 A 75 Advanced Data Mining TDDD 41 Data Mining Clustering and Association Analysis http: //www. ida. liu. se/~732 A 75 http: //www. ida. liu. se/~TDDD 41

Teachers n Patrick Lambrix, examiner, lectures Johan Alenlöv, lectures Huanyu Li, labs (TDDD 41) Atieh Khaleghi, labs (TDDD 41, 732 A 75) Dimitra Muna, labs (732 A 75) n Director of studies: Patrick Lambrix n n 2

Course literature Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, 2 nd edition, Morgan Kaufmann, 2006. or Jiawei Han, Micheline Kamber, Jian Pei, Data Mining - Concepts and Techniques, 3 rd edition, Morgan-Kaufmann, 2011. ISBN: 9780123814791 (ROCK missing) n 3

Course literature Articles. n Lab descriptions. n n Slides related to book content: many slides adapted or taken from lecture slides by Jiawei Han and Micheline Kamber 4

Course organization ¨ Basic topics in association analysis and clustering Lectures n Laboratory exercises (sign up in pairs) n ¨ Credit requirements Written examination ONLINE n Laboratory exercises n 5

Connection to other courses n Companion course to Machine learning course ¨ Classification ML Course ¨ Prediction ¨ Association ¨ Clustering analysis TDDD 41/732 A 75 6

Changes wrt last year Update of slides n New lecturer n n For 732 A 75 (since 2018): ¨ Reduction of former course 732 A 61 (15 hp) (no more student presentations and projects) 7

My own interest and research n Modeling of data – Semantic Web ¨ n Ontologies (for Life sciences, animal health, materials design, crime scene investigation, sports analytics) Ontology engineering Ontology alignment (Winner Anatomy track OAEI 2008 / Organizer OAEI tracks since 2013) ¨ Ontology debugging and completion (Founder and organizer Wo. DOOM/Co. De. S 2012 -2016) ¨ Ontology visualization (Founder and organizer VOILA since 2015) ¨ Topics covered in TDDD 43 8

My own interest and research n Sports Analytics Performance measures for players in ice hockey and football; sports data visualization; trajectory prediction in football ¨ https: //www. ida. liu. se/research/sportsanalytics/ ¨ 9 n Former work: knowledge representation, data integration, knowledge-based information retrieval, object-centered databases n http: //www. ida. liu. se/~patla 00/research. shtml

Sports Analytics n 6 hp course in VT 2 n Sign up by sending mail to patrick. lambrix@liu. se MAX 20 participants n n Course page: https: //www. ida. liu. se/~patla 00/courses/SA/ n Approved to be counted in exam of D, IT, U, MSc CS, MSc Stat&ML

Sports Analytics n Lectures n n Introduction to sports analytics Lectures on research at sports analytics group Guest lectures (e. g. , Signality, LHC, other research groups) Credits: n n Presentations by students on topic of choice in sports analytics Project