• The Korean Journal of Archival Studies
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• no.50
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• pp.177-229
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• 2016

Archival reference service is the ultimate goal and outcome of records management. It encompasses a whole range of activities to connect records with the demands for them. Intellectual needs for records are met by the procedure of information disclosure to guarantee the people's right to know and to provide active responses to archival information needs. Thus, it is required to establish an efficient search system by unifying search tools for archives used in information disclosure and sorting out the classification systems and description items according to the archive types. The qualitative enhancement of information disclosure can be expected when there is a harmonious circulation of attributes-such as applicants, records, search tools, and information providers-for the smooth implementation of reading processes in the context of archival reference service. Therefore, the present study holds its significance in the following aspects. First, it presented a picture of pending issues and the reality of reading service processes from an internal perspective by examining the factors and characteristics that influence "reading service."Second, it demonstrated the phenomenon of close interactions among information providers, applicant, search tools, and records in the process of requesting, searching, and providing records. Third, it proposed the need for a total integrated search tool around the pending issues of reading processes at the National Archives of Korea. Fourth, it promoted an understanding of archival information utilization at the working level among information providers. Finally, it showed major differences in the quality of information provision of "reading service" according to the "perceptions" and "attitudes" of information providers.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.3
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• pp.5-33
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• 2018

In this paper, we analyze a user's usage behavior, identify and track search intention and interest field based on the National Science and Technology Standard Classification, and use it to personalize science and technology information. In other words, we sought to satisfy both efficiency and satisfaction in searching for information that users want by improving scientific information search performance. We developed the personalization service of science and technology information and evaluated the suitability and usefulness of personalized information by comparing the search performance between expert experimental group and control group. As a result, the personalization service proposed in this study showed better search performance than comparative service and proved to provide higher usability.

• The Journal of Industrial Distribution & Business
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• v.11 no.6
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• pp.41-53
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• 2020

Purpose: The purpose of this study is to review the previous studies on the characteristics of the image search service provided by using artificial intelligence, the social impact characteristics, and the moderating effect of perceived anthropomorphism, and conduct empirical analysis to identify the constituent factors affecting purchase intention. To clarify. Through this, I tried to present theoretical and practical implications. Research design, data, and methodology: Research design was that characteristics of image search service (ubiquity and information quality) and social impact characteristics (subjective norms, electronic word of mouth marketing) are affected by mediation of satisfaction and flow, therefore, control of perceived anthropomorphism have an effect on purchase intention to increase. For analysis, research conducted literature review, and developed questionnaires, so that EM firm which is a specialized research institute has collected data. This was conducted on 410 people between the 20s and 50s who have mobile shopping experiences. SPSS Statistics 23 and AMOS 23 had been used to perform necessary analysis such as exploratory factor analysis, reliability analysis, feasibility analysis, and structural equation modeling based on this data. Results: first, ubiquity, information quality and subjective norms were found to have a positive effect on purchase intention through satisfaction and flow parameters. Second, satisfaction and flow were found to have a mediating effect between ubiquity, information quality, and subjective norms and purchase intentions. However, there was no mediating effect between eWOM information and purchase intention. Third, perceived anthropomorphism was found to have a moderating effect between information quality and satisfaction, and it was found that there was no moderating effect on the relationship between information quality and flow. Conclusions: The information quality of image search services using artificial intelligence has a positive effect on satisfaction, and it has been found that there is a positive moderate effect of perceived anthropomorphism in this relationship, which may be an academic contribution to the distribution science utilizing artificial intelligence. Therefore, it is possible to propose a distribution strategy that improves purchase intention by utilizing image search service and anthropomorphism in practical business and providing a more enjoyable immersive experience to customers.

• Journal of Korea Multimedia Society
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• v.15 no.2
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• pp.273-280
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• 2012

Recently, our society is affected by frequent occurrence of disaster such as local heavy rain and landslide. So, disaster organization and facility are stepping up their efforts to establish an effective disaster information system. Especially, researches of smartphone based disaster information service are conducted actively because smartphone becomes an ubiquitous to society and has various advantages. However, in general, these services only provide simple disaster information and do not consider several elements that is desired by the situation and conditions. Therefore, this paper establishes efficient disaster information service through implementation of application that connect disaster collection system and ability to search disaster information according the terms desired of user.

• International Journal of Highway Engineering
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• v.16 no.6
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• pp.115-120
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• 2014

PURPOSES : This research describes how to predict the life cycles of fatigue cracking based on NCHRP Report 704 as well as modified harmony search (MHS) algorithm. METHODS : The fatigue cracking regression model of NCHRP Report 704 was used in order to calculate the ESAL (Equivalent Single Axle Load) numbers up to pavement failure, based on using material parameters, composite modulus, and surface pavement thickness. Furthermore, the MHS algorithm was implemented to find appropriate material parameters and other structural conditions given the number of ESALs, which is related to pavement service life. RESULTS : The case studies show that the material and structural parameters can be obtained, resulting in satisfying the failure endurance of asphalt concrete structure, given the number of ESALs. For example, the required ESALs such as one or two millions are targeted to satisfy the service performance of asphalt concrete pavements in this study. CONCLUSIONS : According to the case studies, It can be concluded that the MHS algorithm provides a good tool of optimization problems in terms of minimizing the difference between the required service cycles, which is a given value, and the calculated service cycles, which is obtained from the fatigue cracking regression model.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.1-23
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• 2023

The purpose of this study is to analyze the characteristics of the integrated search services for integrated libraries operated by local governments in Korea. The target of analysis was integrated libraries operated by 25 local governments in Seoul, and the analysis elements were selected from service functions in 12 areas related to integrated search. The results of the study are as follows. First, the integrated library is an association of public libraries and small libraries in autonomous districts and provides integrated search services. The provided integrated search service function, types of bibliographic information, and facets are not diverse. Second, the records in the search results were mostly item types, not title types. Third, enrichment information supplementing book information consists of book introductions, related information, book-related keywords, and loan-related information. Fourth, integrated search shows the form of integrated OPAC based on integrated catalog DB rather than discovery-type search. It concentrates on providing an integrated search for catalog DBs distributed in public libraries or small libraries in the autonomous district. Fifth, most integrated libraries provide similar service types. Based on these results, improvement plans were proposed for domestic public libraries to expect discovery-type integrated search services.

• Journal of KIISE
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• v.44 no.8
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• pp.782-790
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• 2017

The service, 'Hot Search Keywords', provides a list of the most hot search terms of different web services such as Naver or Daum. The service, bases the changes in rank of a specific search keyword on changes in its users' interest. This paper introduces a temporal modelling framework for predicting the rank change of hot search keywords using past rank data and machine learning. Past rank data shows that more than 70% of hot search keywords tend to disappear and reappear later. The authors processed missing rank value, using deletion, dummy variables, mean substitution, and expectation maximization. It is however crucial to calculate the optimal window size of the past rank data. We proposed an optimal window size selection approach based on the minimum amount of time a topic within the same or a differing context disappeared. The experiments were conducted with four different machine-learning techniques using the Naver, Daum, and Nate 'Hot Search Keywords' datasets, which were collected for 2 years.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.533-540
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• 2006

The semantic web environment promise semantic search of heterogeneous data from distributed web page. Semantic search would resuit in an overwhelming number of results for users is increased, therefore elevating the need for appropriate personalized ranking schemes. Culture Finder helps semantic web agents obtain personalized culture information. It extracts meta data for each web page(culture news, culture performance, culture exhibition), perform semantic search and compute result ranking point to base user profile. In order to work efficient, Culture Finder uses five major technique: Machine learning technique for generating user profile from user search behavior and meta data repository, an efficient semantic search system for semantic web agent, query analysis for representing query and query result, personalized ranking method to provide suitable search result to user, upper ontology for generating meta data. In this paper, we also present the structure used in the Culture Finder to support personalized search service.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.37-42
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• 2015

Although online search engine service provide a convenient means to search for information on the World Wide Web, it also poses a risk of disclosing privacy. Regardless of such risk, most of users are neither aware of their personal information being exposed on search results nor how to redress the issue by requesting removal of information. According to the 2015 parliamentary inspection of government offices, many government agencies were criticized for mishandling of personal information and its leakage on online search engine such as Google. Considering the fact that the personal information leakage via online search engine has drawn the attention at the government level, the online search engine and privacy issue needs to be rectified. This paper, by examining current online search engines, studies the degree of personal information exposure on online search results and its underlying issues. Lastly, based on research result, the paper provides a sound policy and direction to the removal of exposed personal information with respect to search engine service provider and user respectively.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.57-66
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• 2022

In this paper, we propose a legal document search method that uses the Sentence-BERT model. The general public who wants to use the legal search service has difficulty searching for relevant precedents due to a lack of understanding of legal terms and structures. In addition, the existing keyword and text mining-based legal search methods have their limits in yielding quality search results for two reasons: they lack information on the context of the judgment, and they fail to discern homonyms and polysemies. As a result, the accuracy of the legal document search results is often unsatisfactory or skeptical. To this end, This paper aims to improve the efficacy of the general public's legal search in the Supreme Court precedent and Legal Aid Counseling case database. The Sentence-BERT model embeds contextual information on precedents and counseling data, which better preserves the integrity of relevant meaning in phrases or sentences. Our initial research has shown that the Sentence-BERT search method yields higher accuracy than the Doc2Vec or TF-IDF search methods.