Management Information Systems Chapter 11 Answer Key Part 2

53) Apple's Siri application is an example of A) neural networks. B) CBR. C) artificial intelligence. D) intelligent agents. E) machine learning. Answer: D 54) Which of the following is not used to capture tacit knowledge? A) expert system B) case-based reasoning C) fuzzy logic D) neural network E) knowledge base Answer: D 55) Which of the following is a type of intelligent technique? A) digital asset management B) case-based reasoning C) computer-aided design D) VRML E) LMS Answer: B 56) Which of the following techniques is used for knowledge discovery? A) expert system B) transaction processing systems C) case-based reasoning D) data mining E) fuzzy logic Answer: D 57) Technology that consists of computer-based systems that attempt to emulate human behavior is called A) fuzzy logic. B) neural networks. C) AI technology. D) genetic algorithms. E) learning management systems. Answer: C 58) An inference engine is A) a strategy for searching the rule base in case-based reasoning. B) the programming environment of an expert system. C) a method of organizing expert system knowledge into chunks. D) a strategy used to search through the rule base in an expert system by forward chaining or backward chaining. E) a programming algorithm used to create a virtual world using VRML. Answer: D 59) Forward chaining is A) a strategy for searching the rule base in an expert system that begins with information entered by the user. B) the programming environment of an expert system. C) a method of organizing expert system knowledge into chunks. D) a strategy for searching the rule base in an expert system that begins with a hypothesis. E) a programming algorithm used to create a virtual world using VRML. Answer: A 60) Backward chaining is A) a strategy for searching the rule base in an expert system that begins with information entered by the user. B) the programming environment of an expert system. C) a method of organizing expert system knowledge into chunks. D) a strategy for searching the rule base in an expert system that begins with a hypothesis. E) a programming algorithm used to create a virtual world using VRML. Answer: D 61) Expert systems A) solve problems too difficult for human experts. B) are based on DO WHILE rules. C) work in very limited domains. D) share characteristics with mainframe computing. E) are used for knowledge discovery. Answer: C 62) Virtually all expert systems deal with problems of A) policy development. B) classification. C) logic and control. D) high complexity. E) imprecise rules. Answer: B 63) Expert systems are expensive and time consuming to maintain because A) their rule base is so complex. B) they rely on equipment that becomes outdated. C) their rules must be reprogrammed every time there is a change in the environment, which in turn may change the applicable rules. D) only the person who created the system knows exactly how it works, and may not be available when changes are needed. E) it is difficult to program at this level of complexity without introducing software bugs. Answer: C 64) In this technique, descriptions of past experiences of human specialists are stored in a database for later retrieval when the user encounters a situation with similar characteristics. A) CBR B) fuzzy logic C) data mining D) LMS E) expert systems Answer: A 65) Your company wants to develop intelligent techniques to create a "smart" oven that can perfectly cook basic foodstuffs, such as roasts and bread, using sensors and minimal input from the user. The system would know the difference between rare, medium rare, medium, and well done roasts. The category of intelligent technique that would describe this system is A) expert system. B) neural network. C) case-based reasoning. D) fuzzy logic. E) genetic algorithm. Answer: D 66) You are an automotive engineer working on an application that will automatically parallel park a car. The intelligent technique you may find most useful is A) case-based reasoning. B) artificial intelligence. C) fuzzy logic. D) expert system. E) a neural network. Answer: C 67) Fuzzy logic is a type of A) data mining. B) neural network. C) intelligent technique. D) business intelligence. E) case-based reasoning. Answer: C 68) Hardware and software that attempt to emulate the processing patterns of the biological brain best describe A) a neural network. B) an expert system. C) case-based reasoning. D) fuzzy logic. E) artificial intelligence. Answer: A 69) Which of the following describes a difference between neural networks and genetic algorithms? A) Genetic algorithms are designed to process large amounts of information. B) Genetic algorithms are a type of knowledge discovery, while neural networks are an intelligent technique. C) Neural networks are programmed to "learn." D) Genetic algorithms are designed to work with small amounts of data, while neural networks can handle large quantities of data. E) Neural networks are a type of machine learning, whereas genetic algorithms are static programs. Answer: C 70) Genetic algorithms A) develop solutions to particular problems using fitness, crossover, and mutation. B) represent knowledge as groups of characteristics. C) do not work for most problems. D) are based on logic. E) seek to emulate a human expert's way of solving problems. Answer: A 71) Software programs that work without direct human intervention to carry out specific tasks for individual users, business processes, or software applications, are called A) intelligent agents. B) intelligent techniques. C) business intelligence. D) AI hybrid systems. E) genetic algorithms. Answer: A 72) What type of intelligent technique helped Procter & Gamble determine the most efficient methods for their trucks to deliver goods? A) fuzzy logic B) intelligent agents C) genetic algorithms D) neural networks E) CBR Answer: B 73) To automate routine tasks to help firms search for and filter information for use in electronic commerce and supply chain management a firm would most likely use A) CAD systems. B) virtual reality systems. C) fuzzy logic systems. D) intelligent agents. E) genetic algorithms. Answer: D 74) ________ is the study of how computer programs can improve their performance without explicit programming. A) Neural networks B) COP C) Genetic algorithms D) Machine learning E) Intelligent techniques Answer: D 75) The terms used in a fuzzy logic system to describe imprecise states or conditions are referred to as A) neural networks. B) membership functions. C) inference engines. D) taxonomies. E) tags. Answer: B 76) Which type of intelligent agent models the behavior of consumers, stock markets, and more, by seeing them as autonomous agents that follow relatively simple rules for interaction? A) agent-based modeling B) MOOC C) augmented reality D) VRML E) genetic algorithm Answer: A 77) The model of human knowledge used by expert systems is referred to as A) the knowledge base. B) CBR. C) a neural network. D) AI. E) an inference engine. Answer: A 78) A(n) ________ is a type of intelligent technique that finds patterns and relationships in massive data sets too large for a human to analyze. A) inference engine B) CAD C) expert system D) genetic algorithm E) neural network Answer: E 79) Systems that integrate different types of techniques, such as genetic algorithms, fuzzy logic, neural networks, and expert systems, into a single application are called ________ systems. A) differential intelligence B) hybrid AI C) machine learning D) enterprise learning E) CAD Answer: B 80) Expert systems are the primary tools used for knowledge discovery. Answer: FALSE 81) Expert systems capture the knowledge of skilled employees in the form of a set of rules in a software system that can be used by others in the organization. Answer: TRUE 82) Expert systems are typically used in business in discrete, highly structured decision-making situations. Answer: TRUE 83) Expert systems work by applying a set of AND/OR rules against a knowledge base, both of which are extracted from human experts. Answer: FALSE 84) Case-based reasoning is not well-suited for diagnostic systems in medicine. Answer: FALSE 85) Fuzzy logic can describe a particular phenomenon or process linguistically and then represent that description in a small number of flexible rules. Answer: TRUE 86) Fuzzy logic systems "learn" patterns from large quantities of data by sifting through data, searching for relationships, building models, and correcting over and over again the model's own mistakes. Answer: FALSE 87) Because neural network applications cannot always explain why they arrive at a particular solution, they are not well suited for use in the medical profession. Answer: FALSE 88) Hybrid AI applications are being implemented in home appliances, such as washing machines. Answer: TRUE 89) Intelligent agents can discover underlying patterns, categories, and behaviors in large data sets. Answer: FALSE 90) What is the difference between a neural network, fuzzy logic, and genetic algorithms? Which would be most useful to an organization of astronomers analyzing gamma ray emissions reaching Earth? Answer: A neural network attempts to emulate the processing patterns of the biological brain. The results are a program that can "learn" by comparing solutions to known problems to sets of data presented to it. Neural networks are used for solving complex, poorly understood problems for which large amounts of data have been collected. Fuzzy logic creates rules that use approximate or subjective values. It describes a particular phenomenon or process linguistically and then represents that logic in a small number of flexible rules. Genetic algorithms are problem-solving methods that use the model of living organisms adapting to their environment. Possible solutions are evaluated, the "best" choices are made, then more possible solutions are created by combining the factors involved in those first "best" choices, and choosing again. The process continues until an optimum solution is reached. These genetic algorithms are useful for finding the optimal solution for a specific problem by examining a very large number of alternative solutions for that problem. Student evaluations will vary. One answer is: I think a neural network would be of most use because of its ability to analyze large amounts of data and find hidden relationships.