• Title/Summary/Keyword: Subject Searching

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Development of Prototype and Model about the Moving Picture Searching System based on MPEG-7 and KEM (MPEG-7과 KEM 기반의 동영상 검색 시스템 모델 및 프로토타입의 개발)

  • Choe, HyunJong
    • The Journal of Korean Association of Computer Education
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    • v.12 no.3
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    • pp.75-83
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    • 2009
  • Moving picture has become the important media in education with expanded e-learning paradigm, but Korea Educational Metadata has limitation about representing information of lots of events and objects in moving picture. Announcing the MPEG-7 specification the information of lots of events and objects in it can be presented in terms of semantic and structural description of moving pictures. In this paper moving picture searching system model that integrates two metadata specifications, such as KEM and MPEG-7, is proposed. In this model one ontology to combine two metadata specifications is designed, and the other ontology about knowledge of a subject matter is added to search efficiently in searching system. As some moving picture data from Edunet were selected and stored in our server, our prototype of searching system using MPEG-7 and KEM shows the results that we are expected.

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A Study on Design and Development of Web Information Collection System Based Compare and Merge Method (웹 페이지 비교통합 기반의 정보 수집 시스템 설계 및 개발에 대한 연구)

  • Jang, Jin-Wook
    • Journal of Information Technology Services
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    • v.13 no.1
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    • pp.147-159
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    • 2014
  • Recently, the quantity of information that is accessible from the Internet is being dramatically increased. Searching the Web for useful information has therefore become increasingly difficult. Thus, much research has been done on web robots which perform internet information filtering based on user interest. If a web site which users want to visit is found, its content is searched by following the searching list or Web sites links in order. This search process takes a long time according as the number of page or site increases so that its performance need to be improved. In order to minimize unnecessary search with web robots, this paper proposes an efficient information collection system based on compare and merge method. In the proposed system, a web robot initially collects information from web sites which users register. From the next visit to the web sites, the web robot compares what it collected with what the web sites have currently. If they are different, the web robot updates what it collected. Only updated web page information is classified according to subject and provided to users so that users can access the updated information quickly.

A Study of Designing the Han-Guel Thesaurus Browser for Automatic Information Retrieval (자동정보검색을 위한 한글 시소러스 브라우저 구축에 관한 연구)

  • Seo, Whee
    • Journal of Korean Library and Information Science Society
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    • v.31 no.2
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    • pp.279-302
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    • 2000
  • This study is to develop a new automatic system for the Korean thesaurus browser by which we can automatically control all the processes of searching queries such as, representation, generation, extension and construction of searching strategy and feedback searching. The system in this study is programmed by Delphi 4.0(PASCAL) and consists of database system, automatic indexing, clustering technique, establishing and expressing thesaurus, and automatic information retrieval technique. The results proved by this system are as follows: 1)By using the new automatic thesaurus browser developed by the new algorithm, we can perform information retrieval, automatic indexing, clustering technique, establishing and expressing thesaurus, information retrieval technique, and retrieval feedback. Thus it turns out that even the beginner user can easily access special terms about the field of a specific subject. 2) The thesaurus browser in this paper has such merits as the easiness of establishing, the convenience of using, and the good results of information retrieval in terms of the rate of speed, degree, and regeneration. Thus, it t m out very pragmatic.

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Trends in Clinical Research of Catgut Embedding for Obesity Treatment (비만 치료에 매선을 이용한 임상 연구 동향 분석)

  • Jung-Sik Park
    • Journal of Korean Medicine Rehabilitation
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    • v.33 no.3
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    • pp.129-134
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    • 2023
  • Objectives The purpose of this study was to review the studies of catgut embedding related to obesity treatment. Methods We searched the papers with key words of obesity and catgut embedding via searching Research Information Sharing Service, DBpia, Koreanstudies Information Service System, Oriental Medicine Advanced Searching Integrated System, Scopus, PubMed. Additional data including study design, study topics, characteristics of participants and treatment, outcomes was extracted from full text of each study. Results There were nine studies about the catgut embedding related to obesity treatment. Five articles were conducted in China, two articles were conducted in Mexico, and two articles was published in Korea. Analysis of seven experimental studies and two observational studies were conducted to describe each research subject, method, and research results. Conclusions More interest and further research will be needed on catgut embedding related to obesity treatment in the Korean medicine to achieve clinical application and to develop treatment protocols for the obesity disease.

A study on the Structure of the Subject Headings (주제명표목의 구조에 관한 연구)

  • 김태수
    • Journal of the Korean Society for information Management
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    • v.14 no.1
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    • pp.77-105
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    • 1997
  • The study confirmed that the methods for expanding headings and combined structures among the headings, subdivisions, qualifiers and inverted terms were diverse, and that the headings used for similar purposes do not have identical structural forms. It is also found that the standard symbols representing generic relationship in theasurus, which are introduced in the list of subject headings, do not show precisely the hiearchical relationship of phrase headings. MeSH in pre-coordinated system will be available for retrieval in the computer environment because it can make a link between headings and subdivisions in searching stage. The changes in retrieval circumstances and the seeking behaviors of the users demand that a new structure of subject headings be developed. It was proposed that the modification of the structure in the Hangul subject headings be essential.

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Development of Extracting System for Meaning·Subject Related Social Topic using Deep Learning (딥러닝을 통한 의미·주제 연관성 기반의 소셜 토픽 추출 시스템 개발)

  • Cho, Eunsook;Min, Soyeon;Kim, Sehoon;Kim, Bonggil
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.14 no.4
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    • pp.35-45
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    • 2018
  • Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

A Study on Developing Facets for Subject Headings in Korea (한국 주제명 표목의 패싯 유형 개발에 관한 연구)

  • Choi, Yoon Kyung;Chung, Yeon-Kyoung
    • Journal of the Korean Society for Library and Information Science
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    • v.49 no.4
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    • pp.179-201
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    • 2015
  • The subject heading is an elaborate access tool for subject browsing and searching in information retrieval environment. The purpose of this study is to suggest the applicable facets to subject headings in Korea. First, the concepts of subject and the definitions of facets were investigated in the literature review. Second, six cases including OCLC's FAST, PRECIS, "Thesaurus construction and use", CC $7^{th}$ edition, BC $2^{nd}$ Edition, and UDC $3^{rd}$ Edition were analyzed to focus on configuration of facets as case studies. Based on the results, twenty-two facets were proposed including Topical, Event, Geography, Chronology, Personal and Corporate Name, Title, Form, Genre, Language, and Person facets as 11 top facets. Also, Topical-Thing/Entity and Topical-Action/Status, Part, Kind, Property, Whole, Material, Patient, Product, By-Product and Agent facets as sub-facets of Topical facet.

ALGORITHMS FOR SOLVING MATRIX POLYNOMIAL EQUATIONS OF SPECIAL FORM

  • Dulov, E.V.
    • Journal of applied mathematics & informatics
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    • v.7 no.1
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    • pp.41-60
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    • 2000
  • In this paper we consider a series of algorithms for calculating radicals of matrix polynomial equations. A particular aspect of this problem arise in author's work. concerning parameter identification of linear dynamic stochastic system. Special attention is given of searching the solution of an equation in a neighbourhood of some initial approximation. The offered approaches and algorithms allow us to receive fast and quite exact solution. We give some recommendations for application of given algorithms.

Rainfall Estimation for Hydrologic Applications

  • Bae, Deg-Hyo;Georgakakos, K.P.;Rajagopal, R.
    • Korean Journal of Hydrosciences
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    • v.7
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    • pp.125-137
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    • 1996
  • The subject of the paper is the selection of the number and location of raingauge stations among existing ones for the computation of mean areal precipitation and for use as input of real-time flow prediction models. The weighted average method developed by National Weather Service was used to compute MAP over the Boone River basin in Iowa with a 40 year daily data set. Two different searching methods were used to find local optimal solutions. An operational rainfall-runoff model was used to determine the optimal location and number of stations for flow prediction.

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Change Acceptable In-Depth Searching in LOD Cloud for Efficient Knowledge Expansion (효과적인 지식확장을 위한 LOD 클라우드에서의 변화수용적 심층검색)

  • Kim, Kwangmin;Sohn, Yonglak
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.171-193
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    • 2018
  • LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.