knowledge representation of statistic domain for cbr application
DESCRIPTION
Knowledge Representation of Statistic Domain For CBR Application. Supervisor : Dr. Aslina Saad Dr. Mashitoh Hashim PM Dr. Nor Hasbiah Ubaidullah. What is statistics. - PowerPoint PPT PresentationTRANSCRIPT
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Knowledge Representation of Statistic Domain For CBR Application
Supervisor :Dr. Aslina Saad
Dr. Mashitoh HashimPM Dr. Nor Hasbiah Ubaidullah
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What is statistics
Statistics is the mathematical science involved in the application of quantitative principles to the collection, analysis, and presentation of numerical data.
Simply put, statistic is a range of procedures for gathering, organizing, analyzing and presenting quantitative data.
(Berman Brown & Saunders, 2007)
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What is statistics
Statistic can be divided into 2 category: Descriptive statistics
• Concerned with quantitative data and the methods for describing them
Inferential statistics• Makes inferences about populations by
analyzing data gathered from samples and deals with methods that enable a conclusion to be drawn from these data
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Importance of statistics in research
Statistical methods and analyses are often used to communicate research findings and to support hypotheses and give credibility to research methodology and conclusions.
Some of the major purposes of statistics are to help us understand and describe phenomena in our world and to help us draw reliable conclusions about those phenomena
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Problem StatementResearch is one of the main activities in
the university environment. It involves many stakeholders including
lecturers and students. Is a major task for Masters and PhD
students. However, the problems encountered is the
lack of knowledge among student and lecturer in the field of statistics to carry out research which involves quantitative method.
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Most students often have difficulties in performing statistical tests on the data collected.
As a result, they have to consult with experts in the field of statistics to determine the steps that should be taken to analyze their findings.
With this study, hopefully this problem can be solved with the tools that will be developed in order to provide guidance to students in performing statistical studies in accordance with the criteria of their findings.
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Research ObjectiveTo represent knowledge in statistic domain
using OWLTo produce generic model of CBR for statistical
test usage in researchTo construct knowledge base for statistical
test usage in research To generate ontology mapping to a database
(ODBA – Ontology Based Data Integration)To develop a prototype CBR application for
statistical test usage in research To apply reasoning for the constructed
knowledge base via the CBR application
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Literature ReviewMany factors must be considered in
determining the statistical tests to be performed on collected data in a study.
It includes types of data, the number of samples, study purposes and many more.
Knowledge of the statistic domain has to be modeled and transformed into some format that works for representing cases which is crucial for the development of a knowledge base for CBR system
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Semantic WebThis can be represented by using semantic
web.
Semantic web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. (Berners-Lee et. al., 2009)
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Motivation behind the semantic web
Difficult to find, present, access or maintain available electronic information on the web
Need for a data representation to enable software products to provide intelligent access to heterogeneous and distributed information
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From semantic web to CBRMain ideas in the semantic web initiative
are ontology, standards and layers.Ontology is a shared conceptualization
which expressed in a true knowledge representation language namely OWL
CBR is an AI technique based on reasoning on stored cases
CBR technique can be applied to do intelligent retrieval on metadata related to statistic domain that have been encoded using semantic web
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Research Methodology
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The methodology of the study will involve several important phases:
Identification Knowledge acquisition to understand domain
problem Problem and solution feature definition
Knowledge Analysis Conceptual Modeling Knowledge Representation
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Construction (Ontology based data Access and CBR application) Building ontology Define ontology using OWL Mapping a database to an ontology Develop a CBR application
System Implementation and Testing Implement reasoning Querying ontology Test whether the application works
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Gannt Chart
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ConclusionWith this research, it is hoped that it will
offer invaluable insight and understanding the usage of CBR concept in representing knowledge in statistics that supports semantic web.