Thạc Sĩ Hash-based approach to data mining

ABSTRACT
Using computer, people can collect data in many types. Thus, many applications
to revealing valuable information have been considered. One of the most
important matters is “to shorten run time” when database become bigger and
bigger. Furthermore, we look for algorithms only using minimum required
resources but are doing well when database become very large.
My thesis, with the subject “hash-based approach to data mining” focuses on the
hash-based method to improve performance of finding association rules in the
transaction databases and use the PHS (perfect hashing and data shrinking)
algorithm to build a system, which helps directors of shops/stores to have a
detailed view about his business. The soft gains an acceptable result when runs
over a quite large database.

TABLE OF CONTENTS
Abstract i
List of tables ii
List of figures iii
List of abbreviate words iv
FOREWORD 1
CHAPTER 1: Introduction 3
1.1 Overview of finding association rules . 3
1.1.1 Problem description . . 4
1.1.2 Problem solution . 5
1.2 Some algorithms in the early state . 5
1.2.1 AIS algorithm . 6
1.2.2 SETM algorithm . 6
1.2.3 Apriori algorithm . . 6
1.3 Shortcoming problems . 10
CHAPTER 2: Algorithms using hash-based approach to find association
rules 11
2.1 DHP algorithm (direct hashing and pruning) 12
2.1.1 Algorithm description . 13
2.1.2 Pseudo-code 14
2.1.3 Example 16
2.2 PHP algorithm (perfect hashing and pruning) . 18
2.2.1 Brief description of algorithm 19
2.2.2 Pseudo-code 20
2.2.3 Example 21
2.3 PHS algorithm (Perfect hashing and database shrinking) . 22
vi
2.3.1 Algorithm description . 23
2.3.2 Pseudo-code 25
2.3.3 Example 25
2.4 Summarize of chapter 28
CHAPTER 3: Experiments . . 31
3.1 Choosing algorithm . 31
3.2 Implement . 32
CONCLUSION . 35
REFERENCES 37