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DATA MINING Presented by Kalyan K Beemanapalli Aditya K Grandhi
Outline <ul><li>Introduction, Definition, Technology Overview </li></ul><ul><li>A Small Example </li></ul><ul><li>Applicat...
Definition, Introduction <ul><li>History of Data Mining </li></ul><ul><li>An information extraction activity whose goal is...
Overview
Technology Overview <ul><li>Association : If a customer buys snacks, there is a 85% probability that the customer will als...
Market Basket Analysis <ul><li>80% of the people who buy milk also buy bread </li></ul><ul><li>On Friday’s, 70% of the men...
Role of Domain Knowledge <ul><li>Informal knowledge about application  </li></ul><ul><li>domain can be formalized into a s...
Applications of Data Mining <ul><li>CRM  - allow you to determine who your  </li></ul><ul><li>best customers are and why. ...
Future Applications <ul><li>Network Intrusion Detection </li></ul><ul><li>Researchers in Computer Science are concentratin...
Business Value <ul><li>Venkataraman’s Architecture: This technology has the potential to affect the Business Scope of an o...
Issues and Concerns <ul><li>Privacy Concerns :  In the light of developments in technology to analyze personal data, publi...
References <ul><li>http://www.aaai.org/AITopics/html/ethics.html </li></ul><ul><li>http://businessintelligence.ittoolbox.c...
Questions?
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"Data Mining"

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  • Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results
  • Knowledge may be recorded in an individual brain or stored in documents, organizational processes, products, facilities and systems
  • CRM  By applying CRM analytics to your marketing strategies, you will gain a comprehensive view of your customers and target the allocation of your marketing resources FORECASTING 
  • Transcript of ""Data Mining""

    1. 1. DATA MINING Presented by Kalyan K Beemanapalli Aditya K Grandhi
    2. 2. Outline <ul><li>Introduction, Definition, Technology Overview </li></ul><ul><li>A Small Example </li></ul><ul><li>Applications </li></ul><ul><li>Future Applications </li></ul><ul><li>Business Value </li></ul><ul><li>Issues and Concerns </li></ul><ul><li>References </li></ul>
    3. 3. Definition, Introduction <ul><li>History of Data Mining </li></ul><ul><li>An information extraction activity whose goal is to discover hidden facts contained in databases. </li></ul><ul><li>Statistical Analysis Vs Data Mining </li></ul><ul><li>Data mining, in many ways, is fundamentally the adaptation of machine learning techniques to business applications. </li></ul>
    4. 4. Overview
    5. 5. Technology Overview <ul><li>Association : If a customer buys snacks, there is a 85% probability that the customer will also buy soft drinks or beer. </li></ul><ul><li>Classification : Classifications look at the behavior and attributes of already determined groups </li></ul><ul><li>Sequence : a person who buys a washing machine may also buy a clothes dryer within six months with a probability of 0.7 </li></ul><ul><li>Clustering : Clustering divides items into groups based on the similarities the data mining tool finds </li></ul>
    6. 6. Market Basket Analysis <ul><li>80% of the people who buy milk also buy bread </li></ul><ul><li>On Friday’s, 70% of the men who bought diapers also bought beer. </li></ul><ul><li>What is the relationship between diapers and beer? </li></ul><ul><li>Walmart could trace the reason after doing a small survey! </li></ul>
    7. 7. Role of Domain Knowledge <ul><li>Informal knowledge about application </li></ul><ul><li>domain can be formalized into a set of </li></ul><ul><li>Domain Knowledge Elements </li></ul><ul><li>What is Domain Knowledge? </li></ul><ul><li>Why Domain Knowledge is relevant in </li></ul><ul><li>the case of Data Mining? </li></ul><ul><li> The present algorithms just mine the data and </li></ul><ul><li>ask domain experts to decide the </li></ul><ul><li>interestingness of the results. </li></ul><ul><li> Can Data mining algorithms be improved to </li></ul><ul><li>use the knowledge possessed by </li></ul><ul><li>domain experts? </li></ul>Knowledge
    8. 8. Applications of Data Mining <ul><li>CRM - allow you to determine who your </li></ul><ul><li>best customers are and why. </li></ul><ul><li>Forecasting - Forecasting tools allow users to collect data, find patterns in that data and then predict future events or behaviors </li></ul><ul><li>Online Fraud Detection </li></ul><ul><li>e-Business Intelligence </li></ul><ul><li>The list is not exhaustive………. </li></ul>
    9. 9. Future Applications <ul><li>Network Intrusion Detection </li></ul><ul><li>Researchers in Computer Science are concentrating on including the domain knowledge into the data mining algorithms </li></ul><ul><li>Example: Exploring the HR domain in an organization </li></ul>
    10. 10. Business Value <ul><li>Venkataraman’s Architecture: This technology has the potential to affect the Business Scope of an organization </li></ul><ul><li>Amazon’s case : </li></ul><ul><li> 20% for advertisement; 80% for customer experience </li></ul>
    11. 11. Issues and Concerns <ul><li>Privacy Concerns : In the light of developments in technology to analyze personal data, public concerns regarding privacy are rising – PPDM workshop </li></ul><ul><li> Example : An insurance can decide its policy just by knowing your social security number </li></ul><ul><li>Security,Ethical and legal issues: An individual country's legal system may prevent sharing of customer data between a subsidiary and its parent </li></ul><ul><li>Interesting Observation: How do you quantify Privacy? </li></ul>
    12. 12. References <ul><li>http://www.aaai.org/AITopics/html/ethics.html </li></ul><ul><li>http://businessintelligence.ittoolbox.com/ </li></ul><ul><li>http://www.ipc.on.ca/docs/datamine.pdf </li></ul><ul><li>http://www.centeronline.org/knowledge/article.cfm?ID=843&ContentProfileID=123374&Action=searching </li></ul>
    13. 13. Questions?
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