Abstract
With the increasing of database applications, mining interestinginformation from huge databases becomes of most concern and avariety of mining algorithms have been proposed in recent years.As we know, the data processed in data mining may be obtainedfrom many sources in which different data types may be used.However, no algorithm can be applied to all applications due tothe difficulty for fitting data types of the algorithm, so the selectionof an appropriate mining algorithm is based on not only thegoal of application, but als ....etc

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1.Evaluating the potency of the individualized web search
2.Predicting the losing things in the shopping cart
3.Ranking and hinting popular items
4.Watermarking relational data source using seo centered techniques
5.A Cost-Based Technique to Flexible Source Management in Information River Systems
6.Similarity-Profiled Temporary Connections Mining
7.IMine: Catalog Support for Piece Set Mining
8.Compression and Gathering or amassing for Logistic Regression Research in Information Cubes(OLAP)
9.Data exploration over look to look networks
....etc

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PRESENTED BY:
S.Elangovan,


Abstract:
Libraries have a history of taking advantage of technological innovation. In the last few years these efforts have been used to push the boundaries of digital libraries and electronic publishing. Most recently professional librarians are exploring new tools for information management and analysis. The ARL E-Metrics project is exploring ways of standardizing and collecting Data on the use and value of electronic resources. Libraries are becoming partners in university r ....etc

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please give me some topics on text mining for my masters project ....etc

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A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Site-IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 20, NO. 2,

vb.net

Abstract—I
n this paper, we present a complete framework and findings in mining Web usage patterns from Web log files of a real Web site that has all the challenging aspects of real-life Web usage mining, including evolving user profiles and external data describing an ontology of the Web content. Even though the Web site under study is part of a nonprofit organization th ....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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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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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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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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1. Bayesian Data Mining “ finding interestingly large counts in massive tables.
2. Frequent pattern mining for kernel trace data
3. Data Squashing “ compressing large datasets to facilitate statistical analysis.
4. Capturing Best Practice for Microarray Gene Expression
5. Mining Coherent Gene Clusters from Three-Dimensional Microarray Data.
6. A Precise Blocking Method for Record Linkage.
7. Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem
8. FRIL: A Tool for Comparative Record Linkage
9. Detecting ....etc

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