Part B.docx

An effective user behaviour analysis model for online e-commerce websites

MN15-B05

ABSTRACT Online shopping is becoming more and more common in our daily lives. Understanding users’ interests and behaviour is essential in order to adapt ecommerce websites to customers’ requirements. The information about users’ behaviour is stored in the web server logs. The analysis of such information has focused on applying data mining techniques where a rather static characterization is used to model user’s behaviour and the sequence of the actions performed by them is not usually considered. Therefore, incorporating a view of the process followed by users during a session can be of great interest to identify more complex behavioural patterns. To address this issue, this project proposes a linear-temporal logic model checking approach for the analysis of structured e-commerce web logs. By defining a common way of mapping log records according to the e-commerce structure, web logs can be easily converted into event logs where the behaviour of users is captured. Then, different predefined queries can be performed to identify different behavioural patterns that consider the different actions performed by a user during a session. Finally, the usefulness of the proposed approach has been studied by applying it to a real case study of a Spanish e-commerce website. The results have identified interesting findings that have made possible to propose some improvements in the website design with the aim of increasing its efficiency.

Department of CSE

i

VMTW

An effective user behaviour analysis model for online e-commerce websites

MN15-B05

LIST OF FIGURES FIG.NO

NAME

PAGE NO.

Fig1.1

E-commerce website cycle

2

Fig5.1

System Architecture

10

Fig6.1

Use case Diagram

12

Fig6.2

Class Diagram

13

Fig6.3

Sequence Diagram

14

Fig6.4

Flowchart for User

15

Fig6.5

Flowchart for Admin

16

Fig9.1

Home page

42

Fig9.2

Admin login page

43

Fig9.3

Admin home page

44

Fig9.4

Adding new products

45

Fig9.5

Viewing user history

46

Fig9.6

Viewing user frequent visit

47

Fig9.7

Viewing users payments

48

Fig9.8

Registration page for users

49

Fig9.9

User login page

50

Fig9.10

User view page

51

Fig9.11

User selecting products

52

Fig9.12

User payment for a product

53

Fig9.13

Successful transaction

54

Fig8.14

Web personalized and web traversal

55

Fig8.15

Admin analyzes visits

56

Department of CSE

ii

VMTW

An effective user behaviour analysis model for online e-commerce websites

MN15-B05

LIST OF TABLES TAB.NO

NAME

PAGE NO

Tab.1

Test case for user module

41

Tab.2

Test case for admin module

41

s

Department of CSE

iii

VMTW