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Data Mining

Data Mining

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Data Mining

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  1. Data Mining David Eichmann School of Library and Information Science The University of Iowa

  2. Why? • Given enough data represented through enough dimensions, we loose the ability to see the patterns

  3. How? • Decision Trees • Nearest Neighbor Clustering • Neural Networks • Rule Induction • K-Means Clustering

  4. What is it? • The automated extraction of hidden predictive information from databases. • Key points • Automated • Hidden • Predictive

  5. The Typical Process

  6. Evaluation Criteria • Receiver Operating Characteristic Curves

  7. But Nobody Said We Had To Do MATH….

  8. Forms of Data • Structured • Databases • Forms • Semi-Structured • Tables on the Web • Bibliographic citations • Graphs & charts • Unstructured • Full text (e.g., journal articles, physician chart notes) • Images

  9. Text Mining • Corpus now is a collection of text artifacts • Full text when you’ve got it (e.g. newswire) • Metadata when you don’t (e.g. MEDLINE) • The trick then becomes extracting ‘interesting’ relationships between ‘interesting’ entities • Who killed who • Who works for who • Who makes what

  10. The Classic Entities • Persons • Organizations • Places (Geography) • Events

  11. A Newswire Example • APW19981001.0262 [Israel(0.271), Jonathan Pollard (0.153), Benjamin Netanyahu(0.102), Bill Clinton(0.102), United States(0.055), ...] • Persons • Bill Clinton (3) • Jonathan Pollard (8) • Moshe Fogel (2) • Benjamin Netanyahu (2) • Israeli Embassy (1) • Organizations • Cabinet (1) • Places • Israel (16) • United States (5) • Washington (2)

  12. In the Medical/Health Realm • UMLS an excellent framework • Organism • Chemical • Activity • Disease

  13. A MEDLINE Example • Document: 89316090 - Reconstructive surgery in Nicaragua • Provided MeSH Keywords • Human • Nicaragua • Z01.107.169.690 • Surgery, Plastic/* • G02.403.810.788 • Phrases • [Reconstructive, surgery] • [Nicaragua] • [letter] • MeSH Terms • Surgery (1) • G02.403.810.762 • Letter [Publication Type] (1) • Other Phrases • Reconstructive surgery (1)

  14. Concept Extraction Example • “Roman forces under Julius Caesar invade Britain.” (S (NP (NP Roman forces) (PP under (NP Julius Caesar))) (VP invade (NP Britain)) .) • Entity Attributes: • <organization Roman forces> • <person Julias Caesar> • <placename Britain> • Concepts: • <Roman forces - under - Julius Caesar> • <Roman forces - invade - Britain>

  15. And a Small Demo…