24-07-2012, 03:36 PM
Database Management System
Database Management System.docx (Size: 95.69 KB / Downloads: 41)
Introduction
Purpose:
The purpose of PMIS is to propose a technique Dempster-Shafer Theory based Association Rule Mining (DS-ARM), which detects frequently co-occurring groups of items in transactional databases which is used to predict other items that the customer is likely to add to shopping cart. This project optimizes the process of finding frequent items which should be efficient, scalable and detect the important patterns which can easily predict the presence or absence of an item.
Scope:
PMIS focuses on one of the oldest tasks in ARM based on incomplete information about the contents of a shopping cart; we can predict which other items the shopping cart contains. Using the recently proposed data structure of IT-trees, we obtain in a computationally efficient manner, all high-support and high-confidence rules whose antecedents contain at least one item from the incomplete shopping cart.
Overview:
The rest of this SRS is organized as follows: Section 2 gives an overall description of the software. It gives what level of proficiency is expected of the user, some general constraints while making the software and some assumptions and dependencies that are assumed. Section 3 gives specific requirements which the software is expected to deliver. Functional requirements are given by various use cases. Some performance requirements and design constraints are also given.
Database Management System.docx (Size: 95.69 KB / Downloads: 41)
Introduction
Purpose:
The purpose of PMIS is to propose a technique Dempster-Shafer Theory based Association Rule Mining (DS-ARM), which detects frequently co-occurring groups of items in transactional databases which is used to predict other items that the customer is likely to add to shopping cart. This project optimizes the process of finding frequent items which should be efficient, scalable and detect the important patterns which can easily predict the presence or absence of an item.
Scope:
PMIS focuses on one of the oldest tasks in ARM based on incomplete information about the contents of a shopping cart; we can predict which other items the shopping cart contains. Using the recently proposed data structure of IT-trees, we obtain in a computationally efficient manner, all high-support and high-confidence rules whose antecedents contain at least one item from the incomplete shopping cart.
Overview:
The rest of this SRS is organized as follows: Section 2 gives an overall description of the software. It gives what level of proficiency is expected of the user, some general constraints while making the software and some assumptions and dependencies that are assumed. Section 3 gives specific requirements which the software is expected to deliver. Functional requirements are given by various use cases. Some performance requirements and design constraints are also given.