Excavation of Time sliced and Cost based KDD for the lead generation and promotion on B2C/B2B Sales

摘要

Fast advances in information gathering and capacity have empowered associations to collect huge measures of information and hence extracting the only relevant and useful information from large volumes of data is a challenging task. The conventional techniques for data analysis and evaluation cannot be utilized subsequently on the huge measure of the data-set and-so new methods were developed for mining data. Frequent pattern mining algorithms like Apriori, FP-Growth, etc. may sometimes miss the rare but important patterns of a database since they are dealing only with the number of times an item appears in the database. In business environments like retail shops or online markets, identifying the profit-generating items is more important than finding the items which are sold many times. The high utility item set mining with the time cube concept helps us to find the relevant, profit-generating item sets from the transactional data set by performing the calculations using the quantity that is purchased, total cost and unit gain of each item in the database. The concept of time cubes implemented here helps to efficiently deal with the temporal parts of the transactional data set. Considering total cost decides the frequent customer of particular product set. The proposed system is mainly applicable in online markets, FMCG Sectors, large retail stores, and manufacturing plants for improving the revenue by promoting the profit-generating item sets.