• Proceedings of the Korean Society for Information Management Conference
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• 2013.08a
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• pp.119-122
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• 2013

정부 및 기관, 개인에게 부가가치를 제공하는 공공 오픈데이터를 Linked Data로 발행하기 위한 다양한 시도들이 계속되고 있는 현 상황에서, 공공 오픈데이터인 '서울역사박물관의 유물 데이터'를 대상으로 데이터 정제 및 Linked Data로 발행하는 작업을 수행하여 발행 과정에서 나타나는 제약사항들에 대해 검토하였다. 이를 통해 정부 및 각 기관들, 개인이 데이터 발행자 및 이용자의 입장에서 공공 오픈데이터를 활용할 때 고려해야 할 사항들로 데이터 공개 시 데이터에 대한 명확한 설명 제시, 데이터 생애주기에 걸쳐 양질의 데이터 생산 및 공개, 데이터 발행자와 이용자 간의 지속적인 커뮤니케이션을 제언하였다.

• The Journal of Bigdata
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• v.4 no.2
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• pp.195-205
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• 2019

Linked Open Data (LOD) is rated as the best of any kind of data disclosure, and allows you to search related data by linking them in a standard format across the Internet. There is an increasing number of cases in which relevant data are constructed in the LOD form in the global environment, but in the domestic healthcare sector, the disclosure of data in the form of LOD is still at the beginning stage. In this paper, we introduce a case of LOD platform construction that provides services by linking domestic and international related data by LOD method, based on the data of Korean medical research paper data and health care big data linkage platform. Linking all data from each DB into an LOD requires a lot of time and effort, and is basically an infrastructure task that government or public institutions should be in charge of rather than the private sector. In this study, ten domestic and foreign LOD sites were linked with only a portion of each DB, enabling users to link data from various domestic and foreign organizations in a convenient manner.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.89-96
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• 2020

Linked Data allows structured data to be published in a standard way that datasets from various domains can be interlinked. With the rapid evolution of Linked Open Data(LOD), researchers are exploiting it to solve particular problems such as semantic similarity assessment. In this paper, we propose a method, on top of the basic concept of Linked Data Semantic Distance (LDSD), for calculating the Linked Data semantic distance between resources that can be used in the LOD-based recommender system. The semantic distance measurement model proposed in this paper is based on a similarity measurement that combines the LOD-based semantic distance and a new link weight using TF-IDF, which is well known in the field of information retrieval. In order to verify the effectiveness of this paper's approach, performance was evaluated in the context of an LOD-based recommendation system using mixed data of DBpedia and MovieLens. Experimental results show that the proposed method shows higher accuracy compared to other similar methods. In addition, it contributed to the improvement of the accuracy of the recommender system by expanding the range of semantic distance calculation.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.223-229
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• 2022

LinkedIn is one of the most job hunting and career-growing applications in the world. There are a lot of opportunities and jobs available on LinkedIn. According to statistics, LinkedIn has 738M+ members. 14M+ open jobs on LinkedIn and 55M+ Companies listed on this mega-connected application. A lot of vacancies are available daily. LinkedIn data has been used for the research work carried out in this paper. This in turn can significantly tackle the challenges faced by LinkedIn and other job posting applications to improve the levels of jobs available in the industry. This research introduces Text Processing in natural language processing on datasets of LinkedIn which aims to find out the jobs that appear most in a month or/and year. Therefore, the large data became renewed into the required or needful source. This study thus uses Multinomial Naïve Bayes and Linear Support Vector Machine learning algorithms for text classification and developed a trained multilingual dataset. The results indicate the most needed job vacancies in any field. This will help students, job seekers, and entrepreneurs with their career decisions

• Journal of Information Technology Services
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• v.12 no.3
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• pp.311-321
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• 2013

In the community of software engineering, diverse modeling languages are used for representing all relevant information in the form of models. Also many different models such as business model, business process model, product models, interface models etc. are generated through software life cycles. In this situation, models need to be integrated for enterprise integration and enhancement of software productivity. Researchers propose rebuilding models by a specific modeling language, using a intemediate modeling language and using common reference for model integration. However, in the current approach it requires a lot of cost and time to integrate models. Also it is difficult to identify common objects from several models and to update objects in the repository of common model objects. This paper proposes software model integration using metadata model based on Linked data. We verify the effectiveness of the proposed approach through a case study.

• Annual Conference on Human and Language Technology
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• 2012.10a
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• pp.16-20
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• 2012

본 논문에서는 한국어 자연언어처리를 위해 형태소분석기와 구구조 구문분석기와 의존구조 구문분석기를 통합한 하나의 플랫폼을 제공하고, 외국의 다양한 자연언어처리 도구들의 결과물과의 국제적 상호운용성 및 Linked Data를 위한 RDF 형태로의 변환 시스템을 제시한다.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.456-458
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• 2010

시맨틱 웹은 인간 중심의 데이터 표현을 위한 HTML 기반의 기존 웹과는 달리, 웹에서 데이터의 의미를 표현함으로써 다양한 어플리케이션 간의 데이터 상호 교환을 통한 데이터 통합, 재사용성 증대, 기계에 의한 자동화된 처리를 가능하게 해준다. 온톨로지는 데이터의 의미를 표현하기 위한 방법으로 식별자(URI) 기반의 리소스 명명을 통해 데이터의 의미를 표현하며, Linked Data는 RDF 형식의 데이터 간 링크를 통해 웹 데이터 간의 연계 및 활용할 수 있는 환경을 제공해 준다. 본 연구에서는 용어 정보의 효과적인 공유 및 연계를 위한 방법으로, SKOS 기반 용어 온톨로지 모델링을 통해 용어 정보가 Linked Data에 연계되기 위한 방법을 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.57-68
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• 2017

The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.5-24
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• 2021

This study suggested a plan to convert the modern literary data service of the National Library of Korea into linked data-based services. This is not to simply convert the modern literary data service into linked data, which is the current technological trend. This is to create high-quality source data capable of automated machine processing with continuous connection with various external data and information sources in the long term. To this end, in order to revitalize the service of modern literature and to solve the efficient data linkage with related institutions, various overseas library and bibliographic service cases that adopted linked data were first reviewed to draw implications. In addition, based on the reviewed implications, the plan to reorganize the modern literary service in terms of data management, system management, and user service was described in detail.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.285-291
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• 2014

Recently, many researchers have paid attention to the study on generation of new linked data from tables by using linked open data (e.g. RDF, OWL). This paper proposes a new method for such generation of linked data. A pattern-based method intrinsically has a conflict problem among patterns. For instance, several patterns, mapping a single header of a table into different properties of linked data, conflict with each others. Existing studies have sacrificed precision by applying a statistically dominant pattern or have ignored conflicting patterns to increase precision. The proposed method finds appropriate patterns for all headers in a given table by connecting patterns applied to the headers. Experiments using DBPedia and Wikipedia showed results that conflicts of patterns are effectively resolved by the proposed method.