Clonal selection algorithm for learning concept hierarchy from Malay text
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
A hybrid approach for learning concept hierarchy from Malay text using artificial immune network
Natural Computing: an international journal
Review: Formal concept analysis in knowledge processing: A survey on applications
Expert Systems with Applications: An International Journal
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In an effort to develop a tool for automatic ontology building from Malay text based on Formal Concept Analysis, an effective natural language processing (NLP) tool as the pre-processing components is needed. The goal of the study is to investigate whether existing Malay NLP tools can be a viable component to be part of the ontology learning tool. This paper discusses the outcome of the study on three NLP applications. The annotated corpus approach was adopted in this study as deemed suitable for exploratory research. Using the metrics relative subject recall and precision, the results obtained show that statistical modeling technique outperformed pola grammar technique.