• Journal of the Korea Computer Industry Society
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• v.7 no.3
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• pp.227-236
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• 2006

Semantic Web is getting popular to next web environment. Additionally, ontology language research is also activating to represent semantic relation of resource in semantic web. Specially, Ontology language as RDF and DAML+OIL appear on start point of research. But Ontology Language limited to describing characters of resource and to making a clear definition of relation of resource. So W3C suggest OWL at the next standard language for describing resource. OWL supply the lack of representation for RDF and RDF Schema. In this paper, we make Ontology to implement Online Retrieval System using OWL and propose the structure of storing Ontology document at the RDB. The structure support characters of OWL that are equivalent relationship, heterogeneous relationship, inverse relationship, union relationship and one of relationship between classes or properties. In this paper, we classify the extended elements for OWL from RDF Schema. And we propose the method of storing OWL using RDB for interoperability with many applications based on RDB. Finally, implement the storage and retrieval system based on OWL to provide advanced search function.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.249-274
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• 1998

It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.209-217
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• 2019

In this paper, the purpose of this paper is to lay the foundation for the search system by using and building an online search engine suitable for the search domain and enabling search, conversion, integration and sharing of information. It is to use the ontology to infer hierarchical relationships, deduce objects based on that layer, and extract attributes to search areas that are relevant to the data that the user wants. In order to search for information in this way, the information search system was implemented by entering key words related to 'qualifications'. The implemented system arranged the meaning and relationship of each attribute online so that the general public can search information quickly, easily, and accurately. In addition, the implementation results were compared with two different search engines. Comparable search engines are Naver and Daum, the two major search engines. The search engine of this study, which was built using an ontology suitable for the search domain to perform searches using the semantic web, was evaluated to have excellent results. However, it is thought that a more formalized online location is necessary to increase the accuracy and reliability of search engines and to include more comprehensive categories of search terms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.171-177
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• 2011

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.

• Journal of Information Technology Services
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• v.17 no.1
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• pp.135-153
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• 2018

E-Card Service for Child Nutrition Program is one of the main public policy services nowadays. In case of inconvenience during the use of the e-cards, it is recommended to cooperate with related organizations in order to promptly handle and provide guidance, and thoroughly manage child feeding service such as hygiene, nutrition and kindness etc. To do so, it is very important to provide food service that meets local actual conditions and children's needs in a cost effective manner for the underage who are worried about the poorly-fed by understanding the pattern of child feeding e-card service. Hence. this paper aims to investigate how child feeding e-card service efficiently provides meals according to the local situation and children's needs through big data analysis and to propose a method of identifying welfare conditions according to the purpose of service with actual application examples. The results suggest that, first of all, this study is able to judge appropriateness of public institution's policy in a timely and repetitive manner through non-standard data analysis such as Naver News and transaction data. Secondly, this paper proposes a multi-layered analysis framework, which performs online open data analysis to detect policy issues, visualizes retrieval and preprocessing of real data, and performs abnormal pattern recognition. These will be worthy of reference to other similar projects.

• Journal of Information Science Theory and Practice
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• v.5 no.4
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• pp.6-25
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• 2017

In this paper, a large-scale study on users' understanding of search-based advertising is presented. It is based on (1) a survey, (2) a task-based user study, and (3) an online experiment. Data were collected from 1,000 users representative of the German online population. Findings show that users generally lack an understanding of Google's business model and the workings of search-based advertising. 42% of users self-report that they either do not know that it is possible to pay Google for preferred listings for one's company on the SERPs or do not know how to distinguish between organic results and ads. In the task-based user study, we found that only 1.3 percent of participants were able to mark all areas correctly. 9.6 percent had all their identifications correct but did not mark all results they were required to mark. For none of the screenshots given were more than 35% of users able to mark all areas correctly. In the experiment, we found that users who are not able to distinguish between the two results types choose ads around twice as often as users who can recognize the ads. The implications are that models of search engine advertising and of information seeking need to be amended, and that there is a severe need for regulating search-based advertising.

• Journal of Home Health Care Nursing
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• v.25 no.2
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• pp.127-138
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• 2018

Purpose: This study aimed to provide an overview of the present status of start-up literacy. Methods: The study selected literature from KoreaMed, RISS (Research Information Sharing Service), KISS (Korean studies Information Service System), KISTI (Korea Institute of Science and Technology Information), Ovid-MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase, and Cochrane Library DB. Start-up curricula were collected from the homepage of nursing schools in Korea and the USA. Their contents were searched using Massive Open Online Course (MOOC) platforms; KOCW, K-MOOC, and Coursera. Results: Fifteen articles were selected through a systematic literature review. The main themes of nursing start-up were "driver," "barrier," "required competency," and "importance of education." The courses contained business planning, finance, marketing, leadership, and entrepreneurship. The main contents of MOOCs were similar. Conclusion: The results indicate the necessity to develop multi-scope nursing start-up education programs. Nursing start-up models integrated with appropriate business knowledge and skills in health care settings are needed. This study can be used as a guideline to design start-up education programs in nursing.

• Genomics & Informatics
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• v.11 no.4
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• pp.289-291
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• 2013

Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The molecular understanding of HPV proteins has significant connotation for understanding their intrusion in the host and designing novel protein vaccines and anti-viral agents, etc. Genomic, proteomic, structural, and disease-related information on HPV is available on the web; yet, with trivial annotations and more so, it is not well customized for data analysis, host-pathogen interaction, strain-disease association, drug designing, and sequence analysis, etc. We attempted to design an online reserve with comprehensive information on HPV for the end users desiring the same. The Human Papillomavirus Proteome Database (hpvPDB) domiciles proteomic and genomic information on 150 HPV strains sequenced to date. Simultaneous easy expandability and retrieval of the strain-specific data, with a provision for sequence analysis and exploration potential of predicted structures, and easy access for curation and annotation through a range of search options at one platform are a few of its important features. Affluent information in this reserve could be of help for researchers involved in structural virology, cancer research, drug discovery, and vaccine design.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.987-999
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• 2017

Extraction of influential people from their respective domains has attained the attention of scholastic community during current epoch. This study introduces an innovative interaction strength metric for retrieval of the most influential users in the online social network. The interactive strength is measured by three factors, namely re-tweet strength, commencing intensity and mentioning density. In this article, we design a novel algorithm called IPRank that considers the communications from perspectives of followers and followees in order to mine and rank the most influential people based on proposed interaction strength metric. We conducted extensive experiments to evaluate the strength and rank of each user in the micro-blog network. The comparative analysis validates that IPRank discovered high ranked people in terms of interaction strength. While the prior algorithm placed some low influenced people at high rank. The proposed model uncovers influential people due to inclusion of a novel interaction strength metric that improves results significantly in contrast with prior algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.601-605
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• 2009

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Millions of users have integrated these sites into their daily practices to communicate with online people. In this paper, we propose an efficient face annotation and retrieval system under SNS. Since the system needs to deal with a huge database which consists of an increasing users and images, both effectiveness and efficiency are required, In order to deal with this problem, we propose a face annotation classifier which adopts an online learning and social decomposition approach. The proposed method is shown to have comparable accuracy and better efficiency than that of the widely used Support Vector Machine. Consequently, the proposed framework can reduce the user's tedious efforts to annotate face images and provides a fast response to millions of users.