MIS 302F Chapter 6: LE01: introduction to data mining

• School: UT-Austin
• Department: Management Information Systems
• Course: MIS 302F
• Professor: Tuttle John

Document Summary

: accumulating massive amounts of structured and unstructured data: examples and uses of data mining, grocery store: what do customers typically buy together ( ) so they can advertise, display items, and target consumers: uses of data mining include. Predicting behavior in the future: social networks and data mining, extracting emotions from text. Extract positive/negative sentiment from positive or negative emotions: who are the people who buy niche products, key concepts: uses of data mining, uses of data mining. : identifies common characteristics of customers who buy the same products from your company. : predicts which customers are likely to leave a company and go to a competitor deviations to be concerned with. : examining patterns in your purchases and seeing if there are any. : identifies which prospects should be included in a mailing list to obtain the highest response rate. : predicts what someone accessing a website is most likely interested in seeing commonly purchased together.