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ISYS 370 Artificial Intelligence for Information Systems 2004 Professor: Dr. Rosina Weber

ISYS 370 Artificial Intelligence for Information Systems 2004 Professor: Dr. Rosina Weber. Topics of Papers. Expert Systems Interpreting facial expressions Ramp activity Turbine diagnostics Loan underwriting Case-based reasoning GE plastics Project management

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ISYS 370 Artificial Intelligence for Information Systems 2004 Professor: Dr. Rosina Weber

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  1. ISYS 370Artificial Intelligence for Information Systems 2004Professor: Dr. Rosina Weber

  2. Topics of Papers • Expert Systems • Interpreting facial expressions • Ramp activity • Turbine diagnostics • Loan underwriting • Case-based reasoning • GE plastics • Project management • Case-based collaborative web-search • Hybrid recommender systems • Search • University timetable • NFL • Scheduling train crew/hospital nurses • Scheduling Earth Observing Satellites • Machine Learning, Data Mining • ILSA • Skin grading • Link discovery to detect terrorist plots • PTV • Chinese calligraphy • Automatic Detection of Steganography • Neural Networks • Handwriting recognition • Software testing • Genetic Algorithms • Gene expression and metabolic profiles • Network Design and Planning • Natural Language Processing • NL for customer service • Online Essay Evaluation • Branching Storylines in Virtual Reality Environments for Leadership Development

  3. Expert Systems Knowledge acquisition working memory (short-term mem/information) expertproblem knowledgebase (e.g.,framesand methods) userI n t e r f a c e inferenceengine (agenda) expertsolution explanation generalknowledge

  4. CBR methodology RETRIEVE case base RETAIN REUSE REVISE

  5. knowledge based systems • Expert Systems, Case-based Reasoning • financial advise • medical diagnosis, credit analysis • case-based reasoning systems for forecasting, case retrieval, prescription of diet, exercise • knowledge management systems • creativity, planning, forecast, recommender, personalization, argumentation, mediation, tutoring systems (education), • HICAP • Immersive Training Environments with virtual reality

  6. NLU demo http://www.sls.lcs.mit.edu/sls/whatwedo/applications/jupiter.html 1-888-573-8255 NL Understanding • Speech recognition • intonation, pronunciation, speed • Natural Language Processing • syntactic , semantic , pragmatic analysis Natural Language Generation • intention, generation, speech synthesis

  7. natural language • natural language interfaces • machine translation • text understanding to analyze patterns & trends • summarization, information extraction

  8. Problem Solving by Search • use of algorithms • planning, design, optimization, scheduling • solution space to search • games

  9. Machine Learning • analyze trends in any domain, knowledge discovery in databases and text, e.g., data mining • classification and clustering, collaborative filtering

  10. Genetic Algorithms • Improves quality of solutions produced by other methods • Feature selection • Evolves solutions • Similar problems as solved by search algorithms

  11. Neural Networks Applications • predict movement of stocks, currencies, etc., from previous data; • pattern recognition, e.g., penmanship, voice, brain activity patterns of motor areashttp://www.txtwriter.com/Onscience/Articles/ratrobot.html • to recognize signatures made (e.g. in a bank) with those stored; • Diagnosis of equipment, disease, images (MRI), etc. • Pronunciation (rules with many exceptions) • Credit assignment • Vehicle driving • Quality Control - Attaching a camera or sensor to the end of a production process to automatically inspect for defects. • Target Recognition from video and/or infrared image data • Detect fraudulent credit card transactions

  12. Necessary grounds for computer understanding • Ability to represent knowledge and reason with it. • Perceive equivalences and analogies between two different representations of the same entity/situation. • Learning and reorganizing new knowledge. • From Peter Jackson (1998) Introduction to Expert systems. Addison-Wesley third edition. Chapter 2, page 27.

  13. Artificial Intelligence Artificial Intelligence is the field of study dedicated to the study and design of computational models that perform “complex” tasks. These tasks may entail use of knowledge, reasoning, or physical abilities.

  14. AI tasks • planning • scheduling • design • prediction • control • monitoring • analysis • vision • moving • reading &understanding • diagnosis • configuration • categorization • classification • creativity • discovery • speech recognition & synthesis • obstacle avoidance • NL generation • NL understanding

  15. AI tasks and AI problems AI problems are seen as such because they are solved through the performance of AI tasks • AI problem is natural language, whereas related AI tasks are composition, speech, reading and understanding • Examples of AI problems can be mechanical or medical diagnosis and the AI task in both is diagnosis

  16. Types of AI tasks • mundane: • face recognition • argumentation • shopping planning • expert: • diet prescription • medical diagnosis • legal argumentation • legal, military, business planning

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