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Vol. 6 No. 3 September 30, 2018 eISSN : 2287-4577 pISSN : 2287-9099 http://www.jistap.org Vol. 6 No. 3 September 30, 2018 06 A Combinational Method to Determining Identical Entities from Heterogeneous Knowledge Graphs 16 Evaluation of Websites of Public Libraries of India under Ministry of Culture: A Webometric Analysis 25 Anonymous and Non-anonymous User Behavior on Social Media: A Case Study of Jodel and Instagram 37 Rediscovering Forgotten Research: Sleeping Beauties at the University of Waterloo 45 Quantifying Quality: Research Performance Evaluation in Korean Universities Indexed/Covered by SCOPUS, LISA, DOAJ, and CrossRef General Information Aims and Scope The Journal of Information Science Theory and Practice (JISTaP) is an international journal that aims at publishing original studies, review papers and brief communications on information science theory and practice. The journal provides an international forum for practical as well as theoretical research in the interdisciplinary areas of information science, such as information processing and management, knowledge organization, scholarly communication and bibliometrics. JISTaP will be published quarterly, issued on the 30th of March, June, September, and December. JISTaP is indexed in the Scopus, Korea Science Citation Index (KSCI) and KoreaScience by the Korea Institute of Science and Technology Information (KISTI) as well as CrossRef. The full text of this journal is available on the website at http://www.jistap.org Indexed/Covered by Publisher Korea Institute of Science and Technology Information 66, Hoegi-ro, Dongdaemun-gu, Seoul, Republic of Korea (T) +82-2-3299-6102 (F) +82-2-3299-6067 E-mail: [email protected] URL: http://www.jistap.org Managing Editor: Suhyeon Yoo, Eungi Kim Copy Editor: Ken Eckert Design & Printing Company: SEUNGLIM D&C 4F, 15, Mareunnae-ro, Jung-gu, Seoul, Republic of Korea (T) +82-2-2271-2581~2 (F) +82-2-2268-2927 E-mail: [email protected] Open Access and Creative Commons License Statement All JISTaP content is Open Access, meaning it is accessible online to everyone, without fee and au-thors, permission. All JISTaP content is published and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/). Under this license, authors reserve the copyright for their content; however, they permit anyone to unrestrictedly use, distribute, and reproduce the content in any medium as far as the original authors and source are cited. For any reuse, redistribution, or reproduction of a work, users must clarify the license terms under which the work was produced. This paper meets the requirements of KS X ISO 9706, ISO 9706-1994 and ANSI/NISO Z39.48-1992 (Permanence of Paper) 2018 Copyright © Korea Institute of Science and Technology Information Editorial Board Co-Editors-in-Chief Gary Marchionini University of North Carolina, USA Dong-Geun Oh Keimyung University, Korea Associate Editor Kiduk Yang Kyungpook National University, Korea Taesul Seo Korea Institute of Science and Technology Information, Korea Managing Editor Suhyeon Yoo Korea Institute of Science and Technology Information, Korea Eungi Kim Keimyung University, Korea Editorial Board Consulting Editors Beeraka Ramesh Babu Lokman I. Meho Sujin Butdisuwan Hur-Li Lee University of Madras, India American University of Beirut, Mahasarakham University, University of Wisconsin- Lebanon Thailand Milwaukee, USA Pia Borlund University of Copenhagen, Jin Cheon Na Folker Caroli P. Rajendran Denmark Nanyang Technological Universitat Hildesheim, SRM University, India University, Singapore Germany France Bouthillier B. Ramesha McGill University, Canada Dan O’Connor Seon Heui Choi Bangalore University, India Rutgers University, USA Korea Institute of Science Kathleen Burnett and Technology Information, Tsutomu Shihota Florida State University, USA Christian Schloegl Korea St. Andrews University, Japan University of Graz, Austria Boryung Ju Joy Kim Ning Yu Louisiana State University, USA Ou Shiyan University of Southern University of Kentucky, USA Nanjing University, China Noriko Kando California, USA Wayne Buente National Institute of Paul Solomon Kenneth Klein University of Hawaii, USA Informatics, Japan University of South Carolina, University of Southern USA Shailendra Kumar California, USA University of Delhi, India Ina Fourie M. Krishnamurthy University of Pretoria, South DRTC, Indian Statistical Mallinath Kumbar Africa University of Mysore, India Institute, India Helen Partridge S.K. Asok Kumar Fenglin Li University of Southern Wuhan University, China The Tamil Nadu Dr Queensland, Australia Ambedkar Law University, Thomas Mandl India Universiat Hildesheim, Germany 2018 Copyright © Korea Institute of Science and Technology Information Table of Contents Vol. 6 No. 3 September 30, 2018 JISTaP Journal of Information Science Theory and Practice• http://www.jistap.org Articles 06 A Combinational Method to Determining Identical Entities from 06 Heterogeneous Knowledge Graphs - Haklae Kim Evaluation of Websites of Public Libraries of India under Ministry of Culture: 16 A Webometric Analysis - Krishna Brahma, Manoj Kumar Verma Anonymous and Non-anonymous User Behavior on Social Media: 25 A Case Study of Jodel and Instagram Regina Kasakowskij, Natalie Friedrich, Kaja J. Fietkiewicz, Wolfgang G. Stock Rediscovering Forgotten Research: Sleeping Beauties at the University of Waterloo 37 - Jeffrey Demaine Quantifying Quality: Research Performance Evaluation in Korean Universities 45 - Kiduk Yang, Hyekyung Lee Call for Paper 61 Information for Authors 62 2018 Copyright © Korea Institute of Science and Technology Information JISTaP http://www.jistap.org Research Paper Journal of Information Science Theory and Practice J Inf Sci Theory Pract 6(3): 06-15, 2018 eISSN : 2287-4577 pISSN : 2287-9099 https://doi.org/10.1633/JISTaP.2018.6.3.1 A Combinational Method to Determining Identical Entities from Heterogeneous Knowledge Graphs Haklae Kim* Korea Institute of Science and Technology Information, Daejeon, Korea E-mail: [email protected] ABSTRACT With the increasing demand for intelligent services, knowledge graph technologies have attracted much attention. Various application-specific knowledge bases have been developed in industry and academia. In particular, open knowledge bases play an important role for constructing a new knowledge base by serving as a reference data source. However, identifying the same entities among heterogeneous knowledge sources is not trivial. This study focuses on extracting and determining exact and precise entities, which is essential for merging and fusing various knowledge sources. To achieve this, several algorithms for extracting the same entities are proposed and then their performance is evaluated using real-world knowledge sources. Keywords: entity consolidation, knowledge extraction, knowledge graph, knowledge creation, knowledge interlinking Open Access Accepted date: July 09, 2018 All JISTaP content is Open Access, meaning it is accessible online to Received date: December 07, 2017 everyone, without fee and authors’ permission. All JISTaP content is published and distributed under the terms of the Creative Commons *Corresponding Author: Haklae Kim Attribution License (http://creativecommons.org/licenses/by/3.0/). Senior Researcher Under this license, authors reserve the copyright for their content; Korea Institute of Science and Technology Information, 245 Daehak-ro, however, they permit anyone to unrestrictedly use, distribute, and Yuseong-gu, Daejeon, 34141, Korea reproduce the content in any medium as far as the original authors and E-mail: [email protected] source are cited. For any reuse, redistribution, or reproduction of a work, users must clarify the license terms under which the work was produced. © Haklae Kim, 2018 A Method to Determine Identical Entities 1. INTRODUCTION identifying the same relationships to extract and generate knowledge from different data sets. Entity consolidation With the increasing demand for intelligent services, for data integration at the instance level has attracted knowledge graph technologies have attracted much interest in the semantic web and linked data communities. attention for applications, ranging from question-answer It refers to the process of identifying same entities across systems to enterprise data integration (Gabrilovich & heterogeneous data sources (Hogan et al., 2012). A problem Usunier, 2016). A number of research efforts have already can be simplified such that different identifiers are used developed open knowledge bases such as DBpedia for identical entities scattered across different datasets in (Lehmann et al., 2009), Wikidata (Vrandecic, 2012), a web of data. Because redundancy causes an increase in YAGO (Suchanek, Kasneci, & Weikum, 2007), and noisy or unnecessary information across a distributed web Freebase (Bollacker, Evans, Paritosh, Sturge, & Taylor, of data, identifying the same items can be advantageous in 2008). Most open knowledge bases heavily use Linked that multiple descriptions of the same entity can mutually Data technologies for constructing, publishing, and complete and complement each other (Enríquez et al., accessing knowledge sources. Linked data is one of the core 2017). concepts of the Semantic Web, also called the Web of Data This study proposes a combinational approach (Bizer, Cyganiak, & Heath, 2007; Gottron & Staab, 2014). for extracting and determining same entities from It involves making relationships such as links between heterogeneous knowledge sources. It
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