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Business Intelligence and Analytics, Chap 11 flashcards |
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  • Artificial intelligence

    The sub field of computer science concerned with symbolic reasoning and problem solving

    Ai

    artificial intelligence

    Automated decision systems

    A business rule based system that uses intelligence to recommend solutions to repetitive decisions

    ADS

    Automated decision systems

    Backward chaining

    A search technique used in production systems that begins with the action clause of the rule and works backwards through a chain of rules in an attempt to find a verifiable set of condition clauses

    Certainty factors

    A popular technique for representing uncertainty in expert systems where the belief in an event is expressed using the experts unique assessment

    Consultation environment

    The part of an expert system that a non expert uses to obtain expert knowledge and advice

    Decision automation systems

    Computer systems that are aimed at building rule - oriented decision modules

    Development environment

    The part of an expert system that a builder uses. It includes the knowledge base and the reference engine

    Expert

    A human being who has developed a high level of proficiency in making judgement any specific, usually narrow, domain

    Expert system

    A computer system that applies reasoning methodologies to knowledge in a specific domain to render advice or recommendations

    ES

    Expert systems

    Expert system shell

    A computer program that facilitates relatively easy implementation of a specific expert system

    Expertise

    The set of capabilities that underlines the performance of human experts

    Explanation subsystem

    The component of an expert system that can explain the system's reasoning and justify its conclusions

    Forward chaining

    A data-driven search in a rule-based system

    Inference engine

    The part of expert system that actually performs the reasoning function

    Inference rules

    Procedural rules. Offer advice on how to solve a problem, given that certain facts are known

    Knowledge acquisition

    The extraction and formulation of knowledge derived from various sources, especially from experts

    Knowledge base

    A collection of facts, rules, and procedures organized into schemas. The assembly of all the information and knowledge about a specific field of interest

    Knowledge engineer

    an artificial intelligence specialist responsible for the technical side of developing an expert system

    Knowledge engineering

    The engineering discipline in which knowledge is integrated into computer systems to solve complex problems that normally require a high level of human expertise

    Knowledge rules

    A collection of if-then rules that represents the deep knowledge about a specific

    Knowledge-based system

    A rule-based system for providing expertise. Identical to an expert system, except that the source of expertise may include documented knowledge

    Knowledge-refining system

    A system that is capable of analyzing its own performance, learning, and improving itself for future consultations

    Production rules

    The most popular form of knowledge for expert systems where atomic pieces of knowledge are represented using simple if-then structures

    Revenue management systems

    Decision making systems used to make optimal price decisions in order to maximize revenue

    Rule-based systems

    A system in which knowledge is represented completely in terms of rules

    Theory of certainty factors

    A theory designed to help incorporate uncertainty into the representation of knowledge for expert systems

    User interface

    The components of a computer system that allows bidirectional communication between the system minutes user

    Deep knowledge

    The knowledge base contains complex knowledge not easily found among non-experts

    Symbolic reasoning

    Knowledge must be represented symbolically and the primary reasoning mechanism must be symbolic

    Self-knowledge

    Have the ability to examine their own reasoning and provide proper explanation as to why a particular conclusion was reached

    Evaluation

    Assess acceptable performance levels. Analyze whether the system would be usable, efficient and cost-effective

    Validation

    Building the right system. Substantiating that the system performs with an acceptable level of accuracy

    Verification

    Building the system right. Substantiating that the system is correctly implemented to its specifications

    Interpretation category of expert systems

    Inferring situation descriptions from observations

    Prediction category of expert systems

    Inferring likely consequences of given situations

    Diagnosis category of expert systems

    Inferring system malfunction from observations

    Design category of expert systems

    Configuring objects under constraints

    Planning category of expert systems

    Developing plans to achieve goals

    Monitoring category of expert systems

    Comparing observations to plans and flagging exceptions

    Debugging category of expert systems

    Prescribing remedies for malfunctions

    Repair category of expert systems

    Executing a plan to administer a prescribed remedy

    Instruction category of expert systems

    Diagnosing, debugging, and correcting student performance

    Control category of expert systems

    Interpreting, predicting, preparing and monitoring system behavior

    Steps in developing expert systems

    Define the nature and scope of the problem, identify proper experts, acquire knowledge, select the building tools, code the system, evaluate the system

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