Abstract:

This paper presents a data clustering method named BIRCH(Balanced Iterative Reducing and Clustering using Hierarchies), and demonstrate that these especially suitable for very large data bases . BIRCH icrementally and dynamically clusters incoming multy dimensional metric data points to trie to produce the best qulity clustering with available recourses (i.e., available memory and time constraints).

BIRCH can typically find a good clustering with a single-scan of the data and improve the quality further with few additiona ....etc

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Abstract


Aim of the project is to implement the Security features that can avoid Data Dictionary attacks in both the server and transmission part. The first part is to control the data dictionary attacks that occur in direct internal way to the server. Graphical based password authentication is implemented where Pixel co-ordinates are fixed as the password. CCP (cued click points) in added for more security. The user can click the pixel points and login to the server. The user is permitted to click the pixel ....etc

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Data Warehouses, Decision Support and Data Mining

A Data Warehouse is a subject-oriented,integrated,time-variant,non-volatile collection of data used in support of management decision making processes.

Subject-Oriented:-
The data warehouse is organized around the key subjects (or high-level entities) of the enterprise.

Major subjects include
a) Customers
b) Patients
c) Students
d) Products
e) Etc.

Data support :-

Stored collection of diverse data
A solution to data integration problem
Single repository of information
Sub ....etc

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Peer-to-peer computing consists of an open-ended network of distributed computational peers, where each peer shares data and services with a set of other peers, called its acquaintances. The peer-to-peer paradigm was initially popularized by file-sharing systems such as Napster and Gnutella, but its basic ideas and principles have now found their way into more critical and complex data-sharing applications like those for electronic medical records and scientific data. In such environments, data sharing poses new challenges mainly due to the lac ....etc

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Integration Of Data mining And Data warehousing Systems
Presented By:
- N.Nagaraju
3/3 M.C.A I Semester
Introduction:
Traditionally, organizations use data tactically - to manage operations. For a competitive edge, strong organizations use data strategically “ to expand the business, to improve profitability, to reduce costs, and to market more effectively. Data mining creates information assets that an organization can leverage to achieve these strategic objectives. Data Mining is t ....etc

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Peer-to-peer computing consists of an open-ended network of distributed computational peers, where each peer shares data and services with a set of other peers, called its acquaintances. The peer-to-peer paradigm was initially popularized by file-sharing systems such as Napster and Gnutella, but its basic ideas and principles have now found their way into more critical and complex data-sharing applications like those for electronic medical records and scientific data. In such environments, data sharing poses new challenges mainly due to the lac ....etc

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HI THIS IS RAJSHREE LANDE STUDING IN FINAL YEAR FROM ANURADHA COLLEGE OF ENGINEERING...
I WANT A PPTS FOR DATA MINIG AND DATA WAREHOUSING....
I SEARCHING BASICS ON DATA MING AND DATA WAREHOUSING...
BUT I CONFUSE WHAT SHOULD BE ACTUAALY ADD IN THAT TOPIC
WHAT PONTS SHOULD BE THERE...
WHAT ARE THE IMPORTANT TOPICS.....
AND I WANT A DEATIL DESCRIPTION ON THIS TOPICS
IF U GET A IDEAS ON THIS TOPIC PLZ UPLOAD AS SOON AS POSSIBLE.....
WATING FOR SOON RPY.......

RAJSH ....etc

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please send some jounals on this topics and detail that how this technology develop and by whom? ....etc

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Data Mining On Multimedia Data

Introduction:

Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analyzes offered by data mining move beyond the analyses of past events provided by retrospective tools typical of dec ....etc

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