Literature Review: E-Commerce Intelligent E-Order Framework

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Added on 2024/06/28

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This literature review examines various data mining techniques applied to structuring intelligent e-order frameworks for e-commerce practices, drawing from five journal papers. It covers topics such as data mining applications in accounting, optimal pricing strategies, customer segmentation, logistics knowledge retrieval, and agricultural research recommendations. The review identifies key techniques, algorithms, and models used in e-commerce, including data mining, artificial intelligence, and neuron-linguistic programming. It also discusses the goals, processes, advantages, and limitations of these solutions, evaluating their value and potential for improving e-commerce practices. Desklib provides access to this and other solved assignments to support student learning.

Literature Review (Secondary Research) Template
Student Name & CSU
ID
Project Topic Title Using data mining techniques in structuring intelligent e-order framework for e-commerce practices
1

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Version 1.0 _ Week 1 (5 Journal Papers from CSU Library)
1
Reference in APA format that will be
in 'Reference List'
Amani, F. A., & Fadlalla, A. M. (2017). Data mining applications in accounting: A review of the
literature and organizing framework. International Journal of Accounting Information Systems, 24,
32-58.
Citation that will be in the content (Amani and Fadlalla, 2017)
URL of the Reference Level of Journal (Q1, Q2, …Qn) Keywords in this Reference
https://www-sciencedirect-
com.ezproxy.csu.edu.au/science/
article/pii/S1467089515300488
Q1  Data mining
 Accounting
 Literature review
 Framework
 Prospective
 Retrospective
The Name of the Current Solution
(Technique/ Method/ Scheme/
Algorithm/ Model/ Tool/ Framework/
... etc )
The Goal (Objective) of this Solution &
What is the Problem that need to be
solved
What are the components of it?
Technique/Algorithm name:
Data mining
Tools:
Managerial accounting domain
Problem:
Data mining having poor quality
sometimes the values or important symbols
are missing such as data size and issues
with data representation. .
Goal:
Analytic hierarchy
variable clustering
2

Applied Area:
e- commerce
To make data more presentable and
accurate which can easily accessible and
useful for learners.
The Process (Mechanism) of this Work; The process steps of the Technique/system
Process Steps Advantage (Purpose of this step) Disadvantage (Limitation/Challenge)
1
Identification:
Identify the source of information
Data mining will help marketing health
industry to predict new campaigns.
It is not safe as well as not secure for
confidential data or medical records in
health industry.
2 Selection
Should select those data points which need
to be analyse extracting those data
Safe for medical records storage N.A.
3 Identification
Identify the key values (such as
classification, summarization and
reprocessing).
Able to get hidden and useful information N.A.
4
Disclosing
Result to be reported after summarization of
data.
Easy to access anywhere according to
comfort zone.
Costly process
3

Validation Criteria (Measurement Criteria)
Dependent Variable Independent Variable
Prospection Clustering
Retrospection Cost management
Input and Output Critical Thinking: Feature of this work, and
Why (Justify)
Critical Thinking: Limitations of the
research current solution, and Why
(Justify)
Input (Data) Output (View)
Data mining input
includes ordering.
Billing
Paying
Need to be finished
the order
Reconciling
The author has just mainly focused on
categorization of data which somehow ignore
the other responsibilities of data mining. These
responsibilities include such as outline and
connection examination which can give great
benefits.
Lack of easy access to an organisation further
the business related process information it is
useful in accounting and managing of work
which is related to data mining.
(Describe the research/current solution) Evaluation Criteria How this research/current solution is
valuable for your project
4

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The current solution relates to the linear and
non-liner support where it can be seen that
these machines are not able to handle the
mining of data efficiently.
Data mining can help to compress a data in a
formative way to make it accessible. It is used
in different areas by which its uses are
differentiated.
Diagram/Flowchart
5

Fig. 1. Figure-Data mining application
6

2
Reference in APA format that will be
in 'Reference List'
Bauer, J., & Jannach, D. (2018). Optimal pricing in e-commerce based on sparse and noisy
data. Decision Support Systems, 106, 53-63.
Citation that will be in the content Bauer & Jannach, 2018
URL of the Reference Level of Journal (Q1, Q2, …Qn) Keywords in this Reference
https://www-sciencedirect-
com.ezproxy.csu.edu.au/science/
article/pii/S016792361730221X
Q1  Negative sequence analysis
 Sequence analysis
 Behavior analytics
 Non-occurring behavior
 Behavior informatics
 Behavior computing
 Pattern mining
The Name of the Current Solution
(Technique/ Method/ Scheme/
Algorithm/ Model/ Tool/ Framework/
... etc )
The Goal (Objective) of this Solution &
What is the Problem that need to be
solved
What are the components of it?
Technique/Algorithm name:
Artificial intelligence
Tools:
Negative sequential patterns (NSP)
Applied Area:
E- commerce
Problem:
Data mining using artificial intelligence is
based on negative sequence based on set of
different theory. To detect problem from
its surface
Goal:
To identify positive patterns which are
easily accessible which can make a real life
Negative sequential candidates (NSC)
7

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large data.
The Process (Mechanism) of this Work; The process steps of the Technique/system
Process Steps Advantage (Purpose of this step) Disadvantage (Limitation/Challenge)
1 Identification
Identify and Understand Your Targeted
Business Initiative
It is used by extremely superior
organizations which can actually cooperate
with the users.
NA
2 Consideration
Identify Key Decisions initiative by artificial
intelligence.
This helps in identifying the purpose of
data mining
Time consuming process
3 1. Predictive Analysis
2. It includes brainstorming of data that might
be better predictors of performance.
It is a very convenient medium to operate. NA
Validation Criteria (Measurement Criteria)
Dependent Variable Independent Variable
Optimization visualization
prediction outlier detection
Input and Output Critical Thinking: Feature of this work, and
Why (Justify)
Critical Thinking: Limitations of the
research current solution, and Why
8

(Justify)
Input (Data) Output (View)
All PSP and their
related hierarchy.
PSP hash table
More patterns are generated through use of this
solution and in improper way which is not up
to the satisfactory result.
E-NSP has been worked with small numbers
of patterns which need to be in a broad way.,
it carries a low minimum aspects.
(Describe the research/current solution) Evaluation Criteria How this research/current solution is
valuable for your project
NSP mining techniques have huge scanning
database and different types of patterns as
well and they all are having different design
and definitions as well.
Should work in an effective approach to
identify the most significant patterns from
NSP.
Diagram/Flowchart
Figure-Regression tree for total mean profit per product
9

3
Reference in APA format that will be
in 'Reference List'
Ballestar, M. T., Grau-Carles, P., & Sainz, J. (2018). Customer segmentation in e-commerce:
Applications to the cashback business model. Journal of Business Research, 88, 407-414.
Citation that will be in the content Ballestar, et. al., 2018
URL of the Reference Level of Journal (Q1, Q2, …Qn) Keywords in this Reference
https://www.google.com/url?
q=https://www-sciencedirect-
com.ezproxy.csu.edu.au/science/
article/pii/
S0148296317304939&sa=D&source=h
angouts&ust=1532265879181000&usg
=AFQjCNGgQBHZQPsqZ_bAN1g6illl
kVNd8w
Q1 Architectures for educational technology system
Human-computer interface
Intelligent tutoring systems
Programming and programming languages
Teaching/learning strategies
The Name of the Current Solution
(Technique/ Method/ Scheme/
Algorithm/ Model/ Tool/ Framework/
... etc )
The Goal (Objective) of this Solution &
What is the Problem that need to be
solved
What are the components of it?
Technique/Algorithm name:
Human-computer interface
Tools:
Intelligent tutoring systems
Applied Area:
Problem:
Every learner has their own mindset such
as different learning, outcomes knowledge
which cannot be treated in a proper way.
Goal:
 Tutorials
 Tests
 Reports
10

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E commerce Distinguishing the uses of implementation
of the hybrid method in tutoring
programming system.
The Process (Mechanism) of this Work; The process steps of the Technique/system
Process Steps Advantage (Purpose of this step) Disadvantage (Limitation/Challenge)
1 Identifying requirements: The requirements
of the process are identified in this step.
It is very flexible with the users
2 Alternates: The alternative designs are built
up.
Good for users who can access commands
easily.
3 Interactive: Developing interactive versions
of the designs.
Uses the fewest system resources
4 Evaluation: Evaluating designs for the
process
There is no need to learn complex
commands/language
5
Validation Criteria (Measurement Criteria)
Dependent Variable Independent Variable
Speed Linear
Accuracy Accelerated
Input and Output Critical Thinking: Feature of this work, and Critical Thinking: Limitations of the
11

Why (Justify) research current solution, and Why
(Justify)
Input (Data) Output (View)
Have to input
symbols in
accordance to
subject.
Observation of
device outcomes
Learners should know that this article has the
information from users to recognize them for
generating the recommendations.
Improvements should be done to make
recommendations hierarchy which is more
effective with huge range of applications.
(Describe the research/current solution) Evaluation Criteria How this research/current solution is
valuable for your project
The proposal extends the huge range of
applications of social tagging and collect
huge range of learning sources.
Result should be satisfactory with the
requirement of learners with positive
approach.
Diagram/Flowchart
12