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Title: Online Index Recommendations For High-Dimensional Databases Using Query Workloads
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Posted By: seminar topics
Created at: Wednesday 17th of March 2010 12:36:20 AM
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Online Index Recommendations For High-Dimensional Databases Using Query Workloads

Scope of this Project:

Best application for this approach is to apply the more time consuming no-constraint analysis in order to determine an initial index set and then apply a lightweight and low control sensitivity analysis for the online query pattern change detection in order to avoid or make the user aware of situations where the index set is not at all effective for the new incoming queries.

Introduction

An increasing number of database applicati ....etc

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Title: mining projected clusters in high dimensional spaces source
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Posted By:
Created at: Wednesday 05th of December 2012 07:02:01 PM
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Title: ONLINE INDEX RECOMMENDATIONS FOR HIGH-DIMENSIONAL DATABASES USING QUERY WORKLOADS
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Posted By: computer science crazy
Created at: Friday 18th of September 2009 12:43:17 AM
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ONLINE INDEX RECOMMENDATIONS FOR HIGH-DIMENSIONAL DATABASES USING QUERY WORKLOADS

Abstract: Usually users are interested in querying data over a relatively small subset of the entire attribute set at a time. A potential solution is to use lower dimensional indexes that accurately represent the user access patterns. If the query pattern change, then the query response using the physical database design that is developed based on a static snapshot of the query workload may significantly degrade To address these issues, we introduce a parameter ....etc

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Title: online index recommendations for high-dimensional databases using query workloads
Page Link: online index recommendations for high-dimensional databases using query workloads -
Posted By: Meghana G
Created at: Sunday 18th of October 2009 02:33:24 AM
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Can anybody help me out to get into the heart of this topic:-/

online index recommendations for high-dimensional databases using query workloads

This project topic is given in ieee 2008. They have only given pretty short abstract.

I am really not able to understand it properly.:huh:

Can anyone suggest some resources for it.....???:D ....etc

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Title: Online Index Recommendations for High-Dimensional Databases Using Query Workloads
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Posted By: gousiya
Created at: Thursday 20th of January 2011 12:06:03 AM
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Title: mining projected clusters in high dimensional spaces java source code
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Posted By:
Created at: Tuesday 26th of March 2013 01:59:21 PM
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Title: projected capacitive touch screen technology
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Posted By: anupamas
Created at: Sunday 21st of February 2010 02:30:17 PM
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I want more information abt the contruction and working of the projected capacitive touch screen technology! ....etc

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Title: Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data
Page Link: Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data -
Posted By: Projects9
Created at: Monday 23rd of January 2012 06:32:45 PM
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Abstract—Discriminative patterns can provide valuable insights into data sets with class labels, that may not be available from the individual features or the predictive models built using them. Most existing approaches work efficiently for sparse or low-dimensional data sets. However, for dense and high-dimensional data sets, they have to use high thresholds to produce the complete results within limited time, and thus, may miss interesting low-support patterns. In this paper, we address the necessity of trading off the completeness of disc ....etc

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Title: high-dimensional databases
Page Link: high-dimensional databases -
Posted By: nramesh
Created at: Tuesday 30th of March 2010 11:23:21 AM
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Title: Monitoring High-Dimensional Data for Failure Detection and Localization in Large-Scal
Page Link: Monitoring High-Dimensional Data for Failure Detection and Localization in Large-Scal -
Posted By: project topics
Created at: Friday 02nd of April 2010 12:44:03 PM
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Abstract”
It is a major challenge to process high-dimensional measurements for failure detection and localization in large-scale computing systems. However, it is observed that in information systems, those measurements are usually located in a low-dimensional structure that is embedded in the high-dimensional space. From this perspective, a novel approach is proposed to model the geometry of underlying data generation and detect anomalies based on that model. We consider both linear and nonlinear data generation models. Two statistics, ....etc

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