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Articles by Mohammad Syafrullah
Total Records ( 2 ) for Mohammad Syafrullah
  Mohammad Syafrullah and Naomie Salim
  Term extraction is one of the layers in the ontology development process, which has the task to extract all the terms contained in the input document automatically. The objective of this process is to generate a list of terms that are relevant to the domain of the input document. In this study, we present a hybrid method for improving the precision term extraction using a combination of Continuous Particle Swarm Optimization (PSO) and Discrete Binary PSO (BPSO) to optimize fuzzy systems. In this method, PSO and BPSO are used to optimize the membership functions and rule sets of fuzzy systems, respectively. The method was applied to the domain of tourism documents and compared with other term extraction methods: TFIDF, Weirdness, GlossaryExtraction and TermExtractor. From the experiment conducted, the combination of PSO-BPSO showed their capability to generate an optimal set of parameters for the fuzzy membership functions and rule sets automatic adjustment. Findings also showed that fuzzy system performance after optimization achieved significant improvements compared with that before optimization and gave better results compared to those four algorithms.
  Mohammad Syafrullah and Naomie Salim
  Problem statement: Term extraction is one of the layers in the ontology development process which has the task to extract all the terms contained in the input document automatically. The purpose of this process is to generate list of terms that are relevant to the domain of the input document. In the literature there are many approaches, techniques and algorithms used for term extraction where each of approaches, techniques and algorithms has the objective to improve the precision of the extracted terms. Approach: We proposed a new approach using particle swarm optimization techniques in order to improve the precision of term extraction results. We choose five features to represent the term score. Results: The approach had been applied to the domain of Islamic documents. We compare our term extraction method with TFIDF, Weirdness, GlossaryExtraction and TermExtractor. Conclusion: The experimental results showed that our proposed approach achieves better precision than those four algorithms.
 
 
 
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