Discuss why a document-term matrix is an example of a data set that hasasymmetric discrete or asymmetric continuous features.
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SUB: Data Mining
1.) For each of the following data sets, explain whether or not data privacy is an important issue.
(a) USA Census data collected from 1900–2000.
(b) IP addresses and visit times of Web users who visit your Website.
(c) Images from Earth-orbiting satellites.
(d) Names and addresses of people from the telephone book.
(e) Names and email addresses collected from the Web.
2.) You are approached by the marketing director of a local company, who believes that he has devised a foolproof way to measure customer satisfaction. He explains his scheme as follows: “It’s so simple that I can’t believe that no one has thought of it before. I just keep track of the number of customer complaints for each product. I read in a data mining book that counts are ratio attributes, and so, my measure of product satisfaction must be a ratio attribute. But when I rated the products based on my new customer satisfaction measure and showed them to my boss, he told me that I had overlooked the obvious, and that my measure was worthless. I think that he was just mad because our best-selling product had the worst satisfaction since it had the most complaints. Could you help me set him straight?”
(a) Who is correct, the marketing director or his boss? If you answered, his boss, what would you do to fix the measure of satisfaction?
(b) What can you say about the attribute type of the original product satisfaction attribute?
3.) Discuss why a document-term matrix is an example of a data set that has asymmetric discrete or asymmetric continuous features.
SUB: Data Mining
1.) For each of the following data sets, explain whether or not data privacy is an important issue.
(a) USA Census data collected from 1900–2000.
(b) IP addresses and visit times of Web users who visit your Website.
(c) Images from Earth-orbiting satellites.
(d) Names and addresses of people from the telephone book.
(e) Names and email addresses collected from the Web.
2.) You are approached by the marketing director of a local company, who believes that he has devised a foolproof way to measure customer satisfaction. He explains his scheme as follows: “It’s so simple that I can’t believe that no one has thought of it before. I just keep track of the number of customer complaints for each product. I read in a data mining book that counts are ratio attributes, and so, my measure of product satisfaction must be a ratio attribute. But when I rated the products based on my new customer satisfaction measure and showed them to my boss, he told me that I had overlooked the obvious, and that my measure was worthless. I think that he was just mad because our best-selling product had the worst satisfaction since it had the most complaints. Could you help me set him straight?”
(a) Who is correct, the marketing director or his boss? If you answered, his boss, what would you do to fix the measure of satisfaction?
(b) What can you say about the attribute type of the original product satisfaction attribute?
3.) Discuss why a document-term matrix is an example of a data set that has asymmetric discrete or asymmetric continuous features.
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