• Title/Summary/Keyword: Library Skills

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Analysis of Field Librarians' Employment Needs and Human Resource Development in Librarianship (사서직 고용현황 및 인력개발에 대한 현장사서 요구 분석)

  • Noh, Younghee;Ahn, In-Ja;Oh, Se-Hoon
    • Journal of the Korean Society for information Management
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    • v.30 no.4
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    • pp.61-91
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    • 2013
  • In order to achieve effective human resource development in LIS fields, it is essential to have strategies to nurture and utilize those human resources, in relation to supply and demand as well a sound legal foundation supporting those strategies. Such strategies and legal foundation can only be developed from a complete knowledge of the current status of human resources in the LIS and related industries. This study, therefore, conducted research on the basic employment status, employment environment, and an overall analysis of related issues, in order to address policy implications on the effectiveness of human resource development in the LIS field. This research included the current status of policy environments that involve social environment, and related institutions and laws, and human resources developments as well as the current requirements of librarians in the field, based on a demand survey of LIS employment. It was found that first, there are three distinguishable factors in LIS employment: a feminization of librarianship, an increase in temporary posts, and a high entering ratio into the library workplace. Second, while there were only little differences in the given tasks between full-time and temporary employees, the differences in salary and welfare were considerably larger. Third, field requirements for librarian education included a mentoring system with field experts, short-term internships, and librarian apprenticeships, while job requirements included internship or apprenticeship, language skills, various license acquisition, and career management. Fourth, librarians with licenses for related organizations held 20% more librarian licenses overall.

Systematic Review of Driving Rehabilitation for Improving On-Road Driving (도로 주행 능력을 향상시키기 위한 운전재활의 체계적 고찰)

  • Park, Jin-Hyuck;Heo, Seo-Yoon;Seo, Jun;Park, Ji-Hyuk
    • Therapeutic Science for Rehabilitation
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    • v.5 no.2
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    • pp.35-47
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    • 2016
  • Objective: The aim of this study was to identify the driving rehabilitation for on-road driving through a systematic review. Methods: We systematically examined papers published in journals from December 2014 to January 2015, using CINAH, Embase, Pubmed, PsycINFO, and The Cochrane Library. Eventually, 15 studies were included in the analyses. Results: The evidence of 15 studies was from levels I, III, and V. The subjects included in the analyses were patients with stroke(40.0%), older driver(20.0%), traumatic brain injury(20.0%), acquired brain injury(13.3%) and spinal cord injury(6.7%). The intervention types were driving simulator training(53.3%), cognitive skills training(26.6%), off-road educational training(6.7%), adaptation of assistive device(6.7%), and behind-the-wheel training(6.7%). The effects of driving rehabilitation were different depending on the types of intervention. However, driving simulator training showed significant improvement of on-road assessments in all studies included this study. Conclusions: Driving rehabilitation for on-road driving has been used in various types. Specially, the effect of the driving simulator training has been proved by many studies. Future studies are to be required with client from a range of diagnostic groups to establish evidence-based interventions and determine their effectiveness in improving on-road driving.

Function of the Korean String Indexing System for the Subject Catalog (주제목록을 위한 한국용어열색인 시스템의 기능)

  • Yoon Kooho
    • Journal of the Korean Society for Library and Information Science
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    • v.15
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    • pp.225-266
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    • 1988
  • Various theories and techniques for the subject catalog have been developed since Charles Ammi Cutter first tried to formulate rules for the construction of subject headings in 1876. However, they do not seem to be appropriate to Korean language because the syntax and semantics of Korean language are different from those of English and other European languages. This study therefore attempts to develop a new Korean subject indexing system, namely Korean String Indexing System(KOSIS), in order to increase the use of subject catalogs. For this purpose, advantages and disadvantages between the classed subject catalog nd the alphabetical subject catalog, which are typical subject ca-alogs in libraries, are investigated, and most of remarkable subject indexing systems, in particular the PRECIS developed by the British National Bibliography, are reviewed and analysed. KOSIS is a string indexing based on purely the syntax and semantics of Korean language, even though considerable principles of PRECIS are applied to it. The outlines of KOSIS are as follows: 1) KOSIS is based on the fundamentals of natural language and an ingenious conjunction of human indexing skills and computer capabilities. 2) KOSIS is. 3 string indexing based on the 'principle of context-dependency.' A string of terms organized accoding to his principle shows remarkable affinity with certain patterns of words in ordinary discourse. From that point onward, natural language rather than classificatory terms become the basic model for indexing schemes. 3) KOSIS uses 24 role operators. One or more operators should be allocated to the index string, which is organized manually by the indexer's intellectual work, in order to establish the most explicit syntactic relationship of index terms. 4) Traditionally, a single -line entry format is used in which a subject heading or index entry is presented as a single sequence of words, consisting of the entry terms, plus, in some cases, an extra qualifying term or phrase. But KOSIS employs a two-line entry format which contains three basic positions for the production of index entries. The 'lead' serves as the user's access point, the 'display' contains those terms which are themselves context dependent on the lead, 'qualifier' sets the lead term into its wider context. 5) Each of the KOSIS entries is co-extensive with the initial subject statement prepared by the indexer, since it displays all the subject specificities. Compound terms are always presented in their natural language order. Inverted headings are not produced in KOSIS. Consequently, the precision ratio of information retrieval can be increased. 6) KOSIS uses 5 relational codes for the system of references among semantically related terms. Semantically related terms are handled by a different set of routines, leading to the production of 'See' and 'See also' references. 7) KOSIS was riginally developed for a classified catalog system which requires a subject index, that is an index -which 'trans-lates' subject index, that is, an index which 'translates' subjects expressed in natural language into the appropriate classification numbers. However, KOSIS can also be us d for a dictionary catalog system. Accordingly, KOSIS strings can be manipulated to produce either appropriate subject indexes for a classified catalog system, or acceptable subject headings for a dictionary catalog system. 8) KOSIS is able to maintain a constistency of index entries and cross references by means of a routine identification of the established index strings and reference system. For this purpose, an individual Subject Indicator Number and Reference Indicator Number is allocated to each new index strings and new index terms, respectively. can produce all the index entries, cross references, and authority cards by means of either manual or mechanical methods. Thus, detailed algorithms for the machine-production of various outputs are provided for the institutions which can use computer facilities.

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Analysis of Twitter for 2012 South Korea Presidential Election by Text Mining Techniques (텍스트 마이닝을 이용한 2012년 한국대선 관련 트위터 분석)

  • Bae, Jung-Hwan;Son, Ji-Eun;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.141-156
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    • 2013
  • Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.