A method for integrating ontologies, contextual variation and rules, and its application to reading material classification

Subakti, Misbakhul Munir Irfan (2017). A method for integrating ontologies, contextual variation and rules, and its application to reading material classification. University of Birmingham. M.Phil.

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Rule-Based Systems (RBSs) are Knowledge-Based Systems whose knowledge is structured by rules. Our idea is to combine Contextual Ontologies (CO) with RBSs to synergise the advantages of both systems. We aim to make the improvements in two fields: (1) ontologies, and (2) RBSs. We aim to improve the accuracy and possibly other types of quality in (1) by thoroughly integrating contextual information into an ontology, rather than having it separated, and to improve RBS performance in (2) by adding contextual ontological processing into RBSs.

ContextOntoRBS has been proposed, where concepts can be varied according to ”contextual concept-variants”, which can be abbreviated to “concept-variants”. We aim to achieve the improvements in both (1) and (2), independently. Reading Material Classification (RMC) has been chosen as the particular test-bed, and the availability of its dataset will be used to evaluate the improvements in (1) and (2) by proposing a new approach for rule-based RMC. RMC is a classification task where the input text is classified into the particular readability graded reading material.

From the evaluation experiments, we do not claim that our proposed method is better than machine-learning-based RMC. ContextOntoRBS’s performance is just on a par with them. Rather than beating machine-learning-based RMC, we aimed to use RMC for showing that the inclusion of the “integrated contextual concept-variants” in ontologies and RBS provides the improvements over not including them. It can be concluded that by integrating contextual information into an ontology and into an RBS, the improvements can be obtained for both fields.

Type of Work: Thesis (Masters by Research > M.Phil.)
Award Type: Masters by Research > M.Phil.
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Computer Science
Funders: None/not applicable
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
URI: http://etheses.bham.ac.uk/id/eprint/7836


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