• Title/Summary/Keyword: 시맨틱 웹 데이터

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An Experimental Study on the Automatic Interlinking of Meaning for the LOD Construction of Record Information (기록정보 LOD 구축을 위한 의미 상호연결 자동화 실험 연구)

  • Ha, Seung-rok;An, Dae-Jin;Yim, Jin-hee
    • Journal of Korean Society of Archives and Records Management
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    • v.17 no.4
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    • pp.177-200
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    • 2017
  • In a new technological environment such as big data and AI, LOD will link record information resources with various data from both inside and outside. At the heart of this connection is the interlinking technology, and interlinked LOD will realize the opening of record information as the highest level of open data. Given the ever-increasing amount of records, automation through interlinking algorithms is essential in building LODs. Therefore, this paper analyzed the structure of record information interlinking with the external data and characteristics of the record information to be considered when interconnecting. After collecting samples from the CAMS data of the National Archives, we constructed a record information's LOD. After that, we conducted a test bed that automatically interlinks the personal information of the record metadata with DBPedia. This confirms the automatic interlinking process and the performance and accuracy of the automation technology. Through the implications of the testbed, we have identified the considerations of the record information resources of the LOD interlinking process.

Design and Implementation of Topic Map Generation System based Tag (태그 기반 토픽맵 생성 시스템의 설계 및 구현)

  • Lee, Si-Hwa;Lee, Man-Hyoung;Hwang, Dae-Hoon
    • Journal of Korea Multimedia Society
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    • v.13 no.5
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    • pp.730-739
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    • 2010
  • One of core technology in Web 2.0 is tagging, which is applied to multimedia data such as web document of blog, image and video etc widely. But unlike expectation that the tags will be reused in information retrieval and then maximize the retrieval efficiency, unacceptable retrieval results appear owing to toot limitation of tag. In this paper, in the base of preceding research about image retrieval through tag clustering, we design and implement a topic map generation system which is a semantic knowledge system. Finally, tag information in cluster were generated automatically with topics of topic map. The generated topics of topic map are endowed with mean relationship by use of WordNet. Also the topics are endowed with occurrence information suitable for topic pair, and then a topic map with semantic knowledge system can be generated. As the result, the topic map preposed in this paper can be used in not only user's information retrieval demand with semantic navigation but alse convenient and abundant information service.

Semantic-based Automatic Open API Composition Algorithm for Easier-to-use Mashups (Easier-to-use 매쉬업을 위한 시맨틱 기반 자동 Open API 조합 알고리즘)

  • Lee, Yong Ju
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.5
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    • pp.359-368
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    • 2013
  • Mashup is a web application that combines several different sources to create new services using Open APIs(Application Program Interfaces). Although the mashup has become very popular over the last few years, there are several challenging issues when combining a large number of APIs into the mashup, especially when composite APIs are manually integrated by mashup developers. This paper proposes a novel algorithm for automatic Open API composition. The proposed algorithm consists of constructing an operation connecting graph and searching composition candidates. We construct an operation connecting graph which is based on the semantic similarity between the inputs and the outputs of Open APIs. We generate directed acyclic graphs (DAGs) that can produce the output satisfying the desired goal. In order to produce the DAGs efficiently, we rapidly filter out APIs that are not useful for the composition. The algorithm is evaluated using a collection of REST and SOAP APIs extracted from ProgrammableWeb.com.

Improving Diversity of Keyword Search on Graph-structured Data by Controlling Similarity of Content Nodes (콘텐트 노드의 유사성 제어를 통한 그래프 구조 데이터 검색의 다양성 향상)

  • Park, Chang-Sup
    • The Journal of the Korea Contents Association
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    • v.20 no.3
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    • pp.18-30
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    • 2020
  • Recently, as graph-structured data is widely used in various fields such as social networks and semantic Webs, needs for an effective and efficient search on a large amount of graph data have been increasing. Previous keyword-based search methods often find results by considering only the relevance to a given query. However, they are likely to produce semantically similar results by selecting answers which have high query relevance but share the same content nodes. To improve the diversity of search results, we propose a top-k search method that finds a set of subtrees which are not only relevant but also diverse in terms of the content nodes by controlling their similarity. We define a criterion for a set of diverse answer trees and design two kinds of diversified top-k search algorithms which are based on incremental enumeration and A heuristic search, respectively. We also suggest an improvement on the A search algorithm to enhance its performance. We show by experiments using real data sets that the proposed heuristic search method can find relevant answers with diverse content nodes efficiently.

Navigator for OWL Ontologies Generated from Relational Databases (관계형 데이터베이스로부터 생성된 OWL 온톨로지를 위한 탐색기)

  • Choi, Ji Woong;Kim, Myung Ho
    • The Journal of the Korea Contents Association
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    • v.14 no.10
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    • pp.438-453
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    • 2014
  • This paper proposes a system to translate an RDB into an OWL ontology which enables the users to navigate the ontology in GUI. In order to accomplish the goals mentioned previously, the system overcame two difficulties. First, our system defines a new mapping algorithm to map between DB elements and ontology ones. Comparing with existing solutions, our algorithm is able to generate ontologies from more DB structures. Second, our system provides the same data generated by a reasoner to the users. Note that this operation does not load ABox ontology on a reasoner. In addition, Tableau-based reasoners have the tractability problem on a large ABox (e.g., large ABoxes translated from DBs practically cannot be served). To solve this, our system internally runs SQL queries to retrieve the same data as the one from a reasoner every time ABox elements are queried.

Scalable RDFS Reasoning using Logic Programming Approach in a Single Machine (단일머신 환경에서의 논리적 프로그래밍 방식 기반 대용량 RDFS 추론 기법)

  • Jagvaral, Batselem;Kim, Jemin;Lee, Wan-Gon;Park, Young-Tack
    • Journal of KIISE
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    • v.41 no.10
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    • pp.762-773
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    • 2014
  • As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.

Constructing a Model for National Authority Control Utilizing VIVO (VIVO를 활용한 국가적 전거구축모델에 관한 연구)

  • Oh, Sam G.;Han, Sangeun;Son, Teaik;Kim, Seonghun
    • Journal of the Korean Society for information Management
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    • v.35 no.3
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    • pp.165-187
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    • 2018
  • Despite repeated efforts to develop a methodological foundation for assembling collaborative authority data in South Korea, issues such as the establishment of a standard authority model and standard authority construction as well as the reconfiguration of existing entities in authority building have prevented such research from generating a cooperative push for nation-wide authority data and progressing toward concrete implementation. The formulation of a collaborative and well-utilized collection of national authority data accordingly calls for 1) a practical approach to supporting both established authority data contributors and newly organized avenues of mutual participation in authority building, 2) committed involvement on the part of national institutions capable of providing the project with sustained assistance, and 3) a standard identification system which allows multiple organizations to merge their data. This study addresses the challenges of the current environment by taking stock of the key components necessary for the creation of collaborative authority data and using a Semantic Web-based interoperable VIVO ontology model to propose a viable national authority data framework.

Ontology and Sequential Rule Based Streaming Media Event Recognition (온톨로지 및 순서 규칙 기반 대용량 스트리밍 미디어 이벤트 인지)

  • Soh, Chi-Seung;Park, Hyun-Kyu;Park, Young-Tack
    • Journal of KIISE
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    • v.43 no.4
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    • pp.470-479
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    • 2016
  • As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

An Exploratory Study on Linking ISAD(G) and CIDOC CRM Using KARMA (KARMA를 활용한 ISAD(G)와 CIDOC CRM 연계에 관한 탐색적 연구)

  • Park, Zi-young
    • Journal of Korean Society of Archives and Records Management
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    • v.18 no.2
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    • pp.189-214
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    • 2018
  • Archival description is considered as a creation and curation process, and the results of the descriptive records can be used for archival information service. Therefore, various archival descriptive standards provide essential guidelines for establishing a semantic and synthetic structure of the archival records. In this study, the structural aspects of the archival descriptive standards were analyzed and an experimental mapping between General International Standard Archival Description (ISAD(G)), the archival standard, and CIDOC Conceptual Reference Model (CIDOC CRM), the domain ontology of cultural heritage field was performed. The data structure of ISAD(G) is examined in advance and mapping was performed using Karma as a platform. It was thus concluded that there is a need to understand the ontology-based mapping method and the event-focused domain ontology. Moreover, developing a CIDOC CRM-compatible archival ontology and restructuring the legacy ISAD(G) are needed.

An Efficient Indexing Scheme Considering the Characteristics of Large Scale RDF Data (대규모 RDF 데이터의 특성을 고려한 효율적인 색인 기법)

  • Kim, Kiyeon;Yoon, Jonghyeon;Kim, Cheonjung;Lim, Jongtae;Bok, Kyoungsoo;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.15 no.1
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    • pp.9-23
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    • 2015
  • In this paper, we propose a new RDF index scheme considering the characteristics of large scale RDF data to improve the query processing performance. The proposed index scheme creates a S-O index for subjects and objects since the subjects and objects of RDF triples are used redundantly. In order to reduce the total size of the index, it constructs a P index for the relatively small number of predicates in RDF triples separately. If a query contains the predicate, we first searches the P index since its size is relatively smaller compared to the S-O index. Otherwise, we first searches the S-O index. It is shown through performance evaluation that the proposed scheme outperforms the existing scheme in terms of the query processing time.