Algorithms for extracting adjacency matrix based on Formal Concept Analysis (FCA)
The desire to achieve a holistic representation of Information Retrieval (IR) with the aim for a human-oriented form of representation has spurred the growth of concept-based IR search techniques such as the Semantic Web technology. However, Semantic Web calls for the use of ontologies for many doma...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/813/1/FH03-FIK-18-13592.jpg http://eprints.unisza.edu.my/813/ |
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| Summary: | The desire to achieve a holistic representation of Information Retrieval (IR) with the aim for a human-oriented form of representation has spurred the growth of concept-based IR search techniques such as the Semantic Web technology. However, Semantic Web calls for the use of ontologies for many domains. Although meaningful and important, ontology development presents great challenges to the developers especially in terms of conceptual dynamics.. This paper is based on a study that attempts to provide an alternative to ontology lookup for Semantic information retrieval. However, the focus of the paper is on a method proposed to extract adjacency matrix from concepts obtained from the theory of Formal Concept Analysis (FCA) using two consecutive algorithms called the Relatedness Algorithm and Adjacency Matrix Algorithm. Consequently, the adjacency matrices obtained could be used in a similarity measure process based on graph theory. The proposed method offers an alternative to specific domain ontology look-up where results from the measure can further be used in concept-based IR process. |
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