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Constructing faceted taxonomy for heterogeneous entities based on object properties in linked data
Zong, Nansu,Kim, Hong-Gee,Nam, Sejin Elsevier 2017 Data & knowledge engineering Vol.112 No.-
<P><B>Abstract</B></P> <P>The interlinking of data across the web, a concept known as Linked Data, fosters opportunities in data sharing and reusability. However, it may also pose some challenges, which includes the absence of concept taxonomies by which to organize heterogeneous entities that are from different data sources and diverse domains. Learning T-Box (Terminology Box) from A-Box (Assertion Box) has been studied to provide users with concept taxonomies, and is considered a better solution than mapping Linked Data sets with published ontologies. Yet, the existing process of automatically generated taxonomies that classify entities in a particular manner can be improved. Thus, this study aims to automatically create a faceted taxonomy to organize heterogeneous entities, enabling varying classifications of entities by diverse sub-taxonomies, to support faceted search and navigation for linked data applications. The authors have developed a framework on which each facet represented by an object property is used to extract portions of data in the data space, and an Instance-based Concept Taxonomy generation algorithm is developed to build a sub-taxonomy. Additionally, the strategies for sub-taxonomy refinement are proposed. Two experiments have been conducted to prove the promising performances of the proposed method in terms of efficiency and effectiveness.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We defined the notions of facet in a faceted taxonomy as well as the concept and its naming strategy for the taxonomy. </LI> <LI> We developed a faceted taxonomy construction algorithm, ICT, based on object properties of instances in Linked Data. </LI> <LI> The experiments show that ICT outperforms FCA-and Subsumption-based method in a single taxonomy construction. (new bullet point) The experiments show a dramatic reduction of the search space with the faceted taxonomy generated. </LI> </UL> </P>
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신문기사정보 패싯 택소노미 구축 방안 - 예술 분야를중심으로 -
장인호 한국도서관·정보학회 2019 한국도서관정보학회지 Vol.50 No.4
Information on newspaper articles were categorized into different topics, and each categories within different topics were developed into a faceted taxonomies model which was combined with fundamental facets. After suggesting the plan to construct such a model, the research of actual faceted taxonomies were conducted. Faceted taxonomies divide information on news articles into different topics(such as politics, economies and others) and combine fundamental facets with categories(for example, politics can be sub-classified into general politics, administration, legal system, and others) and sub-categories. Each sub-categories can be further subdivided. In taxanomies, categories can have hierarchical relationships. Categories-Facets, for example, can be utilized to combine “arts” with “people”, “action”, “event”, “time”, “place” and others. And Sub-category of the classification of “arts“ such as “art,” “music,” “dance” form hierarchical relationships with “arts” and, in turn, can be used for browsing and further inferences. Furthermore, combining category and facets results in hierarchical structure in order of fundamental facets. As for the pilot vocabulary construction, faceted taxonomies of 145 words from news paper articles on the topic of “arts” were constructed using all construction elements covered in this study. 신문기사를 주제 분야별로 나누고, 분야 내에서 각각의 범주들은 기본 패싯과 결합하는 패싯 택소노미 모형을 개발하였으며 구축 방안을 제시하고 패싯 택소노미를 구축하는 연구를 수행하였다. 패싯 택소노미는 신문기사를 주제 분야(정치, 경제 분야 등)로 나누고 범주(정치 분야의 경우, 정치일반, 행정, 사법 등) 및 하위 범주를 기본 패싯과 각각 결합한다. 하위 범주는 더욱 하위 구분할 수 있다. 택소노미는 범주 간의 계층 관계를 가질 수 있으며, 범주-패싯은 예를 들어, “예술”에 대해 ‘사람’, ‘행위’, ‘행사’, ‘시간’, ‘장소’ 등과 결합한다. 그리고 예술의 하위 범주인 ‘미술’, ‘음악’, ‘무용’ 등은 ‘예술’과 계층 관계를 이루어 추론과 브라우징에 활용할 수 있도록 구성하였다. 또한, 범주-패싯 결합은 기본 패싯순으로 계층 구조를 갖는다. 한편, 시험용 어휘 구축은 ‘예술 분야’를 대상으로 용어 145어를 본 연구에서 다루는 모든 구성요소를 포함하는 패싯 택소노미를 구축하고, 디스플레이를 예시하였다.
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