Reference no: EM131721381

In this project, you will be expected to do a comprehensive literature search and survey, select and study a specific topic in one subject area of data mining and its applications in business intelligence and analytics (BIA), and write a research paper on the selected topic by yourself. The research paper you are required to write can be a detailed comprehensive study on some specific topic or the original research work that will have been done by yourself.

Requirements and Instructions for the Research Paper:

1. The objective of the paper should be very clear about subject, scope, domain, and the goals to be achieved.

2. The paper should address the important advanced and critical issues in a specific area of data mining and its applications in business intelligence and analytics. Your research paper should emphasize not only breadth of coverage, but also depth of coverage in the specific area.

3. The research paper should give the measurable conclusions and future research directions (this is your contribution).

4. It might be beneficial to review or browse through about 15 to 20 relevant technical articles before you make decision on the topic of the research project.

5. The research paper can be one of the following types:
a. Literature review papers on data mining techniques and their applications for business intelligence and analytics.
b. Study and examination of data mining techniques in depth with technical details.
c. Applied research that applies a data mining method to solve a real world application in terms of the domain of BIA.

6. The research paper should reflect the quality at certain academic research level.

7. The paper should be about at least 3000-3500 words double space.

8. The paper should include adequate abstraction or introduction, and reference list.

9. Please write the paper in your words and statements, and please give the names of references, citations, and resources of reference materials if you want to use the statements from other reference articles.

10. From the systematic study point of view, you may want to read a list of technical papers from relevant magazines, journals, conference proceedings and theses in the area of the topic you choose.

Classification Methods:

Regression Methods
Multiple Linear Regression Logistic Regression
Ordered Logistic and Ordered Probit Regression Models Multinomial Logistic Regression Model
Poisson and Negative Binomial Regression Models K Nearest Neighbors
Bayesian Classification Naïve Bayes Method

Decision Trees
ID3 (Iterative Dichotomiser 3) C4.5 and C5.0
CART (Classification and Regression Trees) Scalable Decision Tree Techniques

Neural Network-Based Methods Back Propagation
Neural Network Supervised Learning Bayes Belief Network
Deep Learning

Rule-Based Methods
Generating Rules from a Decision Tree Generating Rules from a Neural Net
Generating Rules without Decision Tree or Neural Net Support Vector Machine
Fuzzy Set and Rough Set Methods

Clustering Methods:

Partition Based Methods Squared Error Clustering
K-Means Clustering (Centroid-Based Technique)
K-Medoids Method (Partition Around Medoids, Representative Object-Based Technique) Bond Energy

Hierarchical Methods
Agnes(Agglomerative vs. Divisive Hierarchical Clustering)
BIRCH (Balanced Iterative Reducing and Clustering Using Hierarchies) Chameleon (Hierarchical Clustering using Dynamic Modeling)
CLARANS (Clustering Large Applications Based Upon Randomized Search) CURE (Clustering Using REpresentatives)

Density Based Methods
DBSCAN (Density Based Spatial Clustering of Applications with Noise, Density Based Clustering Based on Connected Regions with High Density)
OPTICS (Ordering Points to Identity the Clustering Structure)
DENCLUE (DENsity Based CLUstEring, Clustering Based on Density Distribution Functions)

Grid-Based Methods
STING (Statistical Information Grid)
CLIQUE (Clustering In QUEst, An Apriori-like Subspace Clustering Method) Probabilistic Model Based Clustering
Clustering Graph and Network Data (For Example, Social Networks) Self-Organized Map Technique
Evaluation and Performance Measurement of Clustering Methods Assessing Clustering Technology
Determining the Number of Clusters Measuring Clustering Quality

Affinity Analysis Association Rule Mining Recommender Systems Collaborative Filtering Evolution Based Methods: Genetic Algorithms Applications:
Data Mining Applications for Business Intelligence and Analytics

Text Mining
Spatial Mining
Temporal Mining
Web Mining

Sample Format of Project Report

1. Title Page

In general, the number of words in the title of report should be limited around 10 words if possible. The title page should have your name, email, contact information, and term date below the paper title.

2. Abstract

The abstract page should summarize the highlight of your project to tell the audience what have been done in the research project.

3. Table of Contents

The TOC part should list all titles of sections and subsections with page numbers.

4. Introduction

This part introduces the audience with necessary information to guide them into the subjects of your research project.

5. Background and Literature Review

6. Statement of the Proposed Research or Study

With the discussion in Background and Literature Review, the proposed research and study can be given in the format of, possibly, Problem Statement or Objective of Study to indicate what to be studied, investigated, researched, and/or achieved from this project.

7. Methodology

Based on the Problem Statement and the objective to be achieved, you may want to elaborate the underline methodology to be used in order to fulfill the research task and achieve the goal of the research/study. If possible, please provide elaboration of rationales in both depth and width.
It is better to use illustrative examples to explain the methodology employed in this project.

8. Experiment Design and Result Analysis (if applicable)

Provide the details of how experiments are designed and conducted, and observation from the experiment. Analysis of experimental results are important based on your observation, understanding, interpretation, etc. with some performance analysis methods.

9. Conclusion

Summarize your research/study by giving some conclusion from the project, and may provide future research/study directions with discussion of potentials.

10. Reference List

11. Appendix (if applicable.)

For style, please make reference to APA Publication Manual, ACM, IEEE publications, CEC Dissertation Guide.