CEE 5244 Lecture Notes - Lecture 42: Los Angeles Times, Marketing Mix, Potato Chip
5 Apr 2016
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Lecture 42: given a set of data points, each having a set of attributes, and a similarity measure among them, find clusters such that. Data points in one cluster are more similar to one another. Data points in separate clusters are less similar to one another: similarity measures: Other problem-specific measures: illustrating clustering, clustering: application 1, market segmentation: Goal: subdivide a market into distinct subsets of customers where any subset may conceivably be selected as a market target to be reached with a distinct marketing mix. Goal: to find groups of documents that are similar to each other based on the important terms appearing in them. Approach: to identify frequently occurring terms in each document. Form a similarity measure based on the frequencies of different terms. Produce dependency rules which will predict occurrence of an item based on occurrences of other items: association rule discovery: application 1, marketing and sales promotion:
