Building knowledge around complex objects using InforBright Data Warehousing technology

There are considerable challenges in analysing and reporting on word-based data. Infobright data warehousing technology was used to build knowledge around qualitative data that are subject to human interpretation. Infobright was chosen as a system for implementing the data set because its rough set...

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Main Authors: Johnson, J., Johnson, Genevieve
Format: Journal Article
Published: SERSC (Science & Engineering Research Support Society 2010
Subjects:
Online Access:http://www.sersc.org/journals/IJDTA/vol3_no2.php
http://hdl.handle.net/20.500.11937/38998
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author Johnson, J.
Johnson, Genevieve
author_facet Johnson, J.
Johnson, Genevieve
author_sort Johnson, J.
building Curtin Institutional Repository
collection Online Access
description There are considerable challenges in analysing and reporting on word-based data. Infobright data warehousing technology was used to build knowledge around qualitative data that are subject to human interpretation. Infobright was chosen as a system for implementing the data set because its rough set based intelligence appears to be extensible with moderate effort to implement the data warehousing requirements for automatic interpretation of word based data. An example of social sciences research data was used for illustration.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:56:49Z
publishDate 2010
publisher SERSC (Science & Engineering Research Support Society
recordtype eprints
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spelling curtin-20.500.11937-389982017-01-30T14:28:53Z Building knowledge around complex objects using InforBright Data Warehousing technology Johnson, J. Johnson, Genevieve qualitative data semantic similarity qualitative data analysis knowledge grid rough set data warehousing WordNet Infobright There are considerable challenges in analysing and reporting on word-based data. Infobright data warehousing technology was used to build knowledge around qualitative data that are subject to human interpretation. Infobright was chosen as a system for implementing the data set because its rough set based intelligence appears to be extensible with moderate effort to implement the data warehousing requirements for automatic interpretation of word based data. An example of social sciences research data was used for illustration. 2010 Journal Article http://hdl.handle.net/20.500.11937/38998 http://www.sersc.org/journals/IJDTA/vol3_no2.php SERSC (Science & Engineering Research Support Society fulltext
spellingShingle qualitative data
semantic similarity
qualitative data analysis
knowledge grid
rough set
data warehousing
WordNet
Infobright
Johnson, J.
Johnson, Genevieve
Building knowledge around complex objects using InforBright Data Warehousing technology
title Building knowledge around complex objects using InforBright Data Warehousing technology
title_full Building knowledge around complex objects using InforBright Data Warehousing technology
title_fullStr Building knowledge around complex objects using InforBright Data Warehousing technology
title_full_unstemmed Building knowledge around complex objects using InforBright Data Warehousing technology
title_short Building knowledge around complex objects using InforBright Data Warehousing technology
title_sort building knowledge around complex objects using inforbright data warehousing technology
topic qualitative data
semantic similarity
qualitative data analysis
knowledge grid
rough set
data warehousing
WordNet
Infobright
url http://www.sersc.org/journals/IJDTA/vol3_no2.php
http://hdl.handle.net/20.500.11937/38998