a) Given the set of transactions in the table, compute the support for itemsets {e}, {b, d), and (b, d, e} by treating each transaction ID as a market basket. Transaction ID 0001 0024 0012 0031 0015 0022 0029 0040 0033 0038 Items Bought {a,d,e} {a,b,c, e} {a, b, d, e} {a, c, d, e} {b, c, e} {b, d, e} {c,d} {a,b,c} {a, d, e} {a,b,e}

a) Given the set of transactions in the table, compute the support for itemsets {e}, {b, d), and (b, d, e} by treating each transaction ID as a market basket. Transaction ID 0001 0024 0012 0031 0015 0022 0029 0040 0033 0038 Items Bought {a,d,e} {a,b,c, e} {a, b, d, e} {a, c, d, e} {b, c, e} {b, d, e} {c,d} {a,b,c} {a, d, e} {a,b,e}

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Concept explainers

Concepts in Designing Database

A database design is the process of data organization based on a database model. The process deals with identifying what data should be stored in a database and how data elements relate to each other.

Entity Relationship Diagram

Complex real-world applications call for large volumes of data. Therefore, it is necessary to build a great database to store data safely and coherently. The ER data model aids in the process of database design. It helps outline the structure of an organization’s database by understanding the real-world interactions of objects related to the data. For example, if a school is tasked to store student information, then analyzing the correlation between the students, subjects, and teachers would help identify how the data needs to be stored.

Question

a) Given the set of transactions in the table, compute the support for itemsets {e}, {b, d), and {b, d, e}
by treating each transaction ID as a market basket.
Transaction ID
0001
0024
0012
0031
0015
0022
0029
0040
0033
0038
Items Bought
{a, d, e}
{a,b,c, e}
{a, b, d, e}
{a, c, d, e}
{b, c, e}
{b, d, e}
{c,d}
{a,b,c}
{a, d, e}
{a,b, e}
b) Use the results in part (a) to compute the confidence for the association rules {b, d} →→ {e} and
{e}-{b, d).

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