13BA451 - SEMINAR ON MANAGING CUSTOMERS

DATA MINING TECHNIQUES

 

R.JEYA SRI 13MBA033

INTRODUCTION TO

DATA MINING

An analytic process designed to explore large amounts of (typically business or market related) data in search for consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the

detected patterns to new subsets of data.

DATA MINING TECHNIQUES

1. StatisticsA study of the collection, analysis, interpretation, presentation, and organization of data.

o Null hypothesis & P-Valueo Histogramo Time serieso Standardized valueso Variance and standard deviationo Chi- square test etc.

DATA MINING TECHNIQUES

o Decision Treeo Cluster Analysiso Artificial Neural Networko Business Intelligenceo Data Stream Miningo Fuzzy Logico Relational Data Miningo Pattern Recognitiomo Nearest Neighbour Algorithmo Statistics

DATA MINING TECHNIQUES 1. Statistics

Example:

DATA MINING TECHNIQUES

2. Decision treesA decision tree is a structure that can be used

to divide up a large collection of records into successively smaller sets of records by applying

a sequence of simple decision rules.

DATA MINING TECHNIQUES

2. Decision trees

Example: Purchase decision making

DATA MINING TECHNIQUES 3. Neural Networks

The processes of learning through cognitive system and capable of predicting new observations from other observations after executing a process of so-called learning from existing data.

DATA MINING TECHNIQUES

3. Neural Networks

Example: Purchase intention determination

DATA MINING TECHNIQUES 4. Nearest Neighbor Algorithm

An approximate algorithm for finding a (possibly) sub-optimal solution to the Traveling salesman problem.

The algorithm is as followso Start at node 1 o Next node will be the closest as-yet-unvisited

one (if there are two or more at the same closest distance, just pick any one of them)

o Go there and repeat 2. and 3. until no more unvisited nodes

o Go home

DATA MINING TECHNIQUES

4. Nearest Neighbor Algorithm

Example:

DATA MINING TECHNIQUES 5. Link Analysis

Link analysis is a data-analysis technique used to evaluate relationships (connections) between nodes.

Key areas of usage: Investigation of criminal activity computer

security analysis, search engine optimization, market research and medical research.

DATA MINING TECHNIQUES 5. Link Analysis

Example: Friend suggestion in Facebook

DATA MINING TECHNIQUES 6. Relational Data mining

Relational data mining algorithms look for patterns among multiple tables (relational

patterns). 

DATA MINING TECHNIQUES 6. Relational Data Mining

Example: Search engines

DATA MINING TECHNIQUES 7. Cluster Analysis

Clustering is the task of grouping a set of objects in such a way that objects in the same group are more similar.

DATA MINING TECHNIQUES 7. Cluster Analysis

Example: Website viewers analysis

DATA MINING TECHNIQUES 8. Business Intelligence

Set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes.

DATA MINING TECHNIQUES 8. Business Intelligence

Example: Information in dashboard

It no longer makes sense to build the "perfect" model on the historical data since whatever was known in the past cannot adequately predict the future because the future is so unlike what has gone before.

CONCLUSION

• Data Mining Techniques For Marketing, Sales, and Customer Relationship Management, Second Edition, Michael J.A. Berry & Gordon S. Linoff

• Managing Customer Relationships: A Strategic Framework, 2nd Edition, Don Peppers and Martha Rogers

• http://www.idi.ntnu.no/~dingsoyr/diploma/• http://www.wisegeek.com/what-is-a-data-mining-agent.htm• http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4983377• http://www.mis.boun.edu.tr/gulser/index_files/DM%20Techniques

%20%26%20CRM_1.pdf• http://www.zentut.com/data-mining/data-mining-techniques/• http://www.sciencedirect.com/science/article/pii/

S0160791X02000386#gr2• http://www.thearling.com/text/dmtechniques/dmtechniques.htm

REFERENCES

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