文章基本信息

标题：B-BabelNet: Business-Specific Lexical Database for Improving Semantic Analysis of Business Process Models
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作者：Endang Wahyu Pamungkas ; Riyanarto Sarno ; Abdul Munif 等
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2017
卷号：15
期号：1
页码：407-414
DOI：10.12928/telkomnika.v15i1.3176
语种：English
出版社：Universitas Ahmad Dahlan
摘要：Similarity calculation between business process models has an important role in managing repository of business process model. One of its uses is to facilitate the searching process of models in the repository. Business process similarity is closely related to semantic string similarity. Semantic string similarity is usually performed by utilizing a lexical database such as WordNet to find the semantic meaning of the word. The activity name of the business process uses terms that specifically related to the business field. However, most of the terms in business domain are not available in WordNet. This case would decrease the semantic analysis quality of business process model. Therefore, this study would try to improve semantic analysis of business process model. We present a new lexical database called B-BabelNet. B-BabelNet is a lexical database built by using the same method in BabelNet. We attempt to map the Wikipedia page to WordNet database but only focus on the word related to the domain of business. Also, to enrich the vocabulary in the business domain, we also use terms in the business-specific online dictionary (businessdictionary.com). We utilize this database to do word sense disambiguation process on business process model activity’s terms. The result from this study shows that the database can increase the accuracy of the word sense disambiguation process especially in particular terms related to the business and industrial domains.
其他摘要：Similarity calculation between business process models has an important role in managing repository of business process model. One of its uses is to facilitate the searching process of models in the repository. Business process similarity is closely related to semantic string similarity. Semantic string similarity is usually performed by utilizing a lexical database such as WordNet to find the semantic meaning of the word. The activity name of the business process uses terms that specifically related to the business field. However, most of the terms in business domain are not available in WordNet. This case would decrease the semantic analysis quality of business process model. Therefore, this study would try to improve semantic analysis of business process model. We present a new lexical database called B-BabelNet. B-BabelNet is a lexical database built by using the same method in BabelNet. We attempt to map the Wikipedia page to WordNet database but only focus on the word related to the domain of business. Also, to enrich the vocabulary in the business domain, we also use terms in the business-specific online dictionary (businessdictionary.com). We utilize this database to do word sense disambiguation process on business process model activity’s terms. The result from this study shows that the database can increase the accuracy of the word sense disambiguation process especially in particular terms related to the business and industrial domains.
关键词：Similarity;Semantic String Similarity; Lexical Database;Business Domain