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ISYS 370Artificial Intelligence for Information Systems

2004

Professor: Dr. Rosina Weber

Topics of Papers

1. Expert Systems 1. Interpreting facial expressions2. Ramp activity3. Turbine diagnostics4. Loan underwriting

2. Case-based reasoning 1. GE plastics 2. Project management3. Case-based collaborative web-search4. Hybrid recommender systems

3. Search 1. University timetable2. NFL3. Scheduling train crew/hospital nurses4. Scheduling Earth Observing Satellites

4. Machine Learning, Data Mining1. ILSA2. Skin grading3. Link discovery to detect terrorist plots4. PTV5. Chinese calligraphy6. Automatic Detection of Steganography

5. Neural Networks1. Handwriting recognition2. Software testing

6. Genetic Algorithms1. Gene expression and metabolic profiles2. Network Design and Planning

7. Natural Language Processing1. NL for customer service2. Online Essay Evaluation3. Branching Storylines in Virtual Reality Environments for Leadership Development

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knowledgebase

(e.g.,framesand methods)

knowledgebase

(e.g.,framesand methods)

explanationexplanation

generalknowledgegeneral

knowledge

userInterface

userInterface

expertproblemexpert

problem

expertsolutionexpert

solution

inferenceengine

(agenda)

inferenceengine

(agenda)

working memory(short-term mem/information)

working memory(short-term mem/information)

Knowledge acquisitionKnowledge acquisition

Expert Systems

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CBR methodology

casebase

RETRIEVE

REU

SE

REVISE

RETA

IN

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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

Microsoft PowerPoint Presentation

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NLU demohttp://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 analysisNatural Language Generation

– intention, generation, speech synthesis

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natural language

• natural language interfaces• machine translation• text understanding to analyze

patterns & trends• summarization, information extraction

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Problem Solving by Search

• use of algorithms – planning, design, optimization, scheduling– solution space to search– games

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Machine Learning

– analyze trends in any domain, knowledge discovery in databases and text, e.g., data mining

– classification and clustering, collaborative filtering

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Genetic Algorithms

• Improves quality of solutions produced by other methods

• Feature selection• Evolves solutions• Similar problems as solved by

search algorithms

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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

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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.

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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.

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AI tasks

• reading &understanding

• diagnosis• configuration• categorization• classification• creativity• discovery

• speech recognition & synthesis

• obstacle avoidance

• NL generation• NL

understanding

• planning• scheduling• design• prediction• control• monitoring• analysis• vision• moving

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AI tasks and AI problemsAI 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

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Types of AI tasks• mundane:

– face recognition– argumentation– shopping planning

• expert:– diet prescription– medical diagnosis– legal argumentation– legal, military, business planning