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Title: On the Design of a Parallel Object-Oriented Data Mining Toolkit

Abstract

As data mining techniques are applied to ever larger data sets, it is becoming clear that parallel processors will play an important role in reducing the turn around time for data analysis. In this paper, we describe the design of a parallel object-oriented toolkit for mining scientific data sets. After a brief discussion of our design goals, we describe our overall system design that uses data mining to find useful information in raw data in an iterative and interactive manner. Using decision trees as an example, we illustrate how the need to support flexibility and extensibility can make the parallel implementation of our algorithms very challenging. As this is work in progress, we also describe the solution approaches we are considering to address these challenges.

Authors:
;
Publication Date:
Research Org.:
Lawrence Livermore National Lab., CA (US)
Sponsoring Org.:
USDOE Office of Defense Programs (DP) (US)
OSTI Identifier:
791750
Report Number(s):
UCRL-JC-138973
TRN: US200304%%527
DOE Contract Number:  
W-7405-Eng-48
Resource Type:
Conference
Resource Relation:
Conference: 6th International Conference on Knowledge Discovery and Data Mining, Boston, MA (US), 08/20/2000--08/23/2000; Other Information: PBD: 17 May 2000
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ALGORITHMS; DATA ANALYSIS; DESIGN; FLEXIBILITY; IMPLEMENTATION; MINING

Citation Formats

Kamath, C, and Cantu-Paz, E. On the Design of a Parallel Object-Oriented Data Mining Toolkit. United States: N. p., 2000. Web.
Kamath, C, & Cantu-Paz, E. On the Design of a Parallel Object-Oriented Data Mining Toolkit. United States.
Kamath, C, and Cantu-Paz, E. Wed . "On the Design of a Parallel Object-Oriented Data Mining Toolkit". United States. https://www.osti.gov/servlets/purl/791750.
@article{osti_791750,
title = {On the Design of a Parallel Object-Oriented Data Mining Toolkit},
author = {Kamath, C and Cantu-Paz, E},
abstractNote = {As data mining techniques are applied to ever larger data sets, it is becoming clear that parallel processors will play an important role in reducing the turn around time for data analysis. In this paper, we describe the design of a parallel object-oriented toolkit for mining scientific data sets. After a brief discussion of our design goals, we describe our overall system design that uses data mining to find useful information in raw data in an iterative and interactive manner. Using decision trees as an example, we illustrate how the need to support flexibility and extensibility can make the parallel implementation of our algorithms very challenging. As this is work in progress, we also describe the solution approaches we are considering to address these challenges.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2000},
month = {5}
}

Conference:
Other availability
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