data mining

PAPER PRESENTATION ON DATA MINING   BY   TEJAS P. SHAHA. (TE CSE) SARVESH R. HIRIKUDE. (TE CSE) Walchand Institute Of Technology ,Solapur :

PAPER PRESENTATION ON DATA MINING BY TEJAS P. SHAHA . ( TE CSE) SARVESH R. HIRIKUDE . ( TE CSE) Walchand Institute Of Technology , Solapur

Index: :

Index: Introduction Categorization of Data Mining Data Mining Process Web Mining Web Usage Mining Web Mining Data Collection Applications Conclusion

Introduction::

Introduction: Mining: Extraction of necessary material from a source field. Data Mining is a collection of complex activities that aims at extracting synthesized and previously unknown information from large databases.

Categorization of Data Mining::

Categorization of Data Mining: Representation of Models and Results  The type of data used. i.e. continuous, discrete, time series, nominal The application type. economic models, biology, genetics, web log mining Pattern attributes. accuracy , precision, interpretability, newness, expressiveness

Data Mining Process::

Data Mining Process:

Web Mining::

Web Mining: As a large and dynamic information source that is structurally complex and ever growing, the World Wide Web (www) is fertile ground for Data Mining Principles , or Web Mining. Categories : Web Contents mining Web hyper link str. Mining Web usage mining

Web Usage Mining::

Web Usage Mining: E-Business T raffic Analysis Advertising Webviz : Popularized Web usage mining of Web transactions.

Web Mining Data Collection::

Web Mining Data Collection: Web servers Clients Proxy Servers Server Databases Web Mining is sensitive to noise, data cleaning methods are necessary

Applications::

Applications: Banking SuperMarket Pharmaceutical Companies An intelligence agency reviews spending patterns and travel data to detect abnormal behavior by its employees. A physician analyzes X-ray images to detect abnormal patterns. AirLine Reservation.

Tools::

Tools: SAS data mining software helps in following ways: It supports DM Process with a broad set of TOOLS. Anticipate resource demands Increase acquisitions Most accurate in Prediction analysis

Conclusion::

Conclusion: Data Mining is an area that will continue to explode during the next decade, presenting endless opportunities and challenges for developers who are finding practical ways to use this emerging technology. Only with a solid grounding in the basics, however, can I.T. professionals hope to make the best use of the answers they get from Data Mining.

Questions and Queries??:

Questions and Queries?? Thank You