assignment 10 - AI and BI + BI and Knowledge Management
Is a simple program that predicts what sides and beverages you may want with your order based on your previous orders and what other users have ordered an example of strong or weak AI? Explain your answer.
his would be an example of Weak AI as it is simply using existing data vs what the person is likely to be feeling that day or any advanced cognition or reasoning.
What is autocategorization (automatic taxonomy)? How can autocategorization software help companies to serve customers and employees?
Autocategorization is automatic classification of information into well-defined categories. It can be done by special software. Companies use autocategorization to support online queries as free-form questions. The questions can come from customers who need help about a product or from employees who connect to a knowledge base remotely. This saves labor because instead of a person, it is software that provides the answer.
What is the difference between the Data Management Module and a Model Management Module in a Decision Support System?
A Data Management Module gathers information and is part of the "intelligence" phase. A model management module on the other hand turns data into useful information. It often uses statistical models such as regressions to find the type of relationship between variables.
What is the difference between a sensitivity analysis and regression analysis?
A sensitivity analysis focuses on how much a particular output changes as a result of another variable changing. A regression analysis is used to find the type of relationship between two variables, and how strong that relationship is.
What is AI, and how is AI related to BI? Give an example.
AI or Artificial Intelligence is the ability of computers to mimic human intelligence aspects such as reasoning, emotional intelligence and cognition. Artificial Intelligence allows companies to build better business intelligence (BI) tools that can more effectively mimic human behavior. For example, having a tool that can predict how much someone will be willing to pay based on their negotiation strategy and body language would be an example of using AI to build BI and price discriminate more effectively (an example of strong AI).
What is the purpose of employee knowledge networks?
Employee knowledge networks direct an employee with an inquiry about a subject to employees who might have expertise in the subject.
What is the purpose of an Expert System (ES)?
The purpose of an ES is to emulate the expertise of a human expert. Expertise is a competitive asset for any business, and by capturing it in software, the business can continue to use the expertise when the expert is no longer available.
Among the models of data mining are sequence analysis, classification, clustering and forecasting. Data mining helps determine whether a person has committed fraud. Which of the four types of analysis is most likely to help do that and why?
Determining if a person committed fraud can be detected by finding if a certain conduct falls into a predefined pattern or not. Their actions can be classified into various buckets, e.g. convenience stores, travel to Europe once a week, etc.
How can an ES be used to report employee fraud to a manager or officer? Think about the information that could be entered in an ES.
ESs can be programmed to compare a set of transactions that an employee carries out and a set of transactions that typically indicate probable fraud. The system automatically tracks the employee behavior through interaction with disbursements (or other systems that allow electronic transfer of money) and compares them with the patterns it incorporates as rules. It reports probable fraud through a message on an officer's computer monitor.
In general, what is the purpose of knowledge management in organizations?
The purpose of knowledge management is to capture knowledge and organize it in a manner that will make it known, available, and easy to retrieve by members of the organization who can use it to save time and money.