Extraction of ObjectProperty-UsageMethod Relation from Web Documents
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This paper aims to extract an ObjectProperty-UsageMethod relation, in particular the HerbalMedicinalProperty-UsageMethod relation of the herb-plant object, as a semantic relation between two related sets, a herbalmedicinal-property concept set and a usage-method concept set from several web documents. ThisHerbalMedicinalProperty-UsageMethod relation benefits people by providing an alternative treatment/solutionknowledge to health problems. The research includes three main problems: how to determine EDU (whereEDU is an elementary discourse unit or a simple sentence/clause) with a medicinal-property/usage-methodconcept; how to determine the usage-method boundary; and how to determine the HerbalMedicinalProperty-UsageMethod relation between the two related sets. We propose using N-Word-Co on the verb phrase withthe medicinal-property/usage-method concept to solve the first and second problems where the N-Word-Cosize is determined by the learning of maximum entropy, support vector machine, and naïve Bayes. We alsoapply naïve Bayes to solve the third problem of determining the HerbalMedicinalProperty-UsageMethodrelation with N-Word-Co elements as features. The research results can provide high precision in theHerbalMedicinalProperty-UsageMethod relation extraction.
Abstract
This paper aims to extract an ObjectProperty-UsageMethod relation, in particular the HerbalMedicinalProperty-UsageMethod relation of the herb-plant object, as a semantic relation between two related sets, a herbalmedicinal-property concept set and a usage-method concept set from several web documents. ThisHerbalMedicinalProperty-UsageMethod relation benefits people by providing an alternative treatment/solutionknowledge to health problems. The research includes three main problems: how to determine EDU (whereEDU is an elementary discourse unit or a simple sentence/clause) with a medicinal-property/usage-methodconcept; how to determine the usage-method boundary; and how to determine the HerbalMedicinalProperty-UsageMethod relation between the two related sets. We propose using N-Word-Co on the verb phrase withthe medicinal-property/usage-method concept to solve the first and second problems where the N-Word-Cosize is determined by the learning of maximum entropy, support vector machine, and naïve Bayes. We alsoapply naïve Bayes to solve the third problem of determining the HerbalMedicinalProperty-UsageMethodrelation with N-Word-Co elements as features. The research results can provide high precision in theHerbalMedicinalProperty-UsageMethod relation extraction.
참고문헌 (16)
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