• Title/Summary/Keyword: Search Terms

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Analysis of Users' Inflow Route and Search Terms of the Korea National Archives' Web Site (국가기록원 웹사이트 유입경로와 이용자 검색어 분석)

  • Jin, Ju Yeong;Rieh, Hae-young
    • Journal of the Korean Society for information Management
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    • v.35 no.1
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    • pp.183-203
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    • 2018
  • As the users' information use environment changes to the Web, the archives are providing more services on the Web than before. This study analyzes the users' recent inflow route and the highly ranked 100 search terms of each month for 10 and half years in the Web site of National Archives of Korea, and suggests suitable information services. As a result of the analysis, it was found out that the inflow route could be divided into access from portal site, by country, from related institutions, and via mobile platform. As a result of analyzing the search terms of users for the last 10 and half years, the most frequently searched term turned out to be 'Land Survey Register', which was also the search term that was searched for with steady interests for 10 and half years. Also, other government documents or official gazettes were of great interests to users. As results of identifying the most frequently searched and steadily searched terms, we were able to categorize the search terms largely in terms of land, Japanese colonial period, the Korean war and relationship of North Korea and South Korea, and records management and use. Based on the results of the analysis, we suggested strengthening connection of the National Archives Web site with portal sites and mobile, and upgrading and improving search services of the National Archives. This study confirmed that the analysis of Web log and user search terms would yield meaningful results that could enhance the user services in archives.

Method for improving search efficiency using relation of anatomical structure from Donguibogam(東醫寶鑑) ("동의보감"에 기재된 인체 용어 관계를 이용한 검색효율성 향상 방법)

  • Song, In-Woo;Lee, Byung-Wook
    • Journal of Korean Medical classics
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    • v.25 no.4
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    • pp.105-113
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    • 2012
  • Objectives : Acquiring information from symptoms is one of the important method to gain clinically available information in korean medicine. Therefore, up to now, study of symptom terms was frequently implemented in promotion of various information project. In data extraction methods using symptom information from DB, information search using synonym and method using ontology is studied and utilized. However, considering concept of symptom has essential information of appeared body area and phenomenon we think that extending synonym and ontology relationship in symptom terms can be useful for search and set to this study. Methods : We collect terms relevant to human body area and structure described in Donguibogam. Synonymous relationship between collected terms is organized. Relationship between collected terms is build to human-body-knowledge table which has form of Concept+Relation+Concept. Type of relationship is limited on a range of expressing content about parts of human body. Result & Conclusion : Search condition is generated automatically using relationship of the upper area in knowledge table contents. Information of next and previous acupuncture point, upper and lower acupuncture point, left and right acupuncture point can be searched using information of acupuncture point location, order, relative position in area, direction in knowledge table contents.

Identifying Similar Overseas Patent Using Word2Vec-Based Semantic Text Analytics (Word2Vec 학습을 통한 의미 기반 해외 유사 특허 검색 방안)

  • Paek, Minji;Kim, Namgyu
    • Journal of Information Technology Services
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    • v.17 no.2
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    • pp.129-142
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    • 2018
  • Recently, the number of patent applications have been increasing rapidly every year as the importance of protecting intellectual property rights becomes more important. Patents must be inventive and have novelty. Especially, the novelty implies that the corresponding invention is not the same as the previous invention. To confirm the novelty, prior art search must be conducted before and after the application. The target of prior art search should include not only Korean patents but also foreign patents. Search of foreign patents should be supported by multilingual search techniques. However, a dictionary-based naive approach shows a limitation because some technical concepts are represented in different terms according to each nation. For example, a Korean term and a Japanese term may not be synonym even though they represent the same technical concept. In this paper, we propose a new method to map semantic similarity between technical terms in Korean patents and Japanese patents. To investigate different representations in each nation for the same technical concept, we identified and analyzed pairs of patents those are mutually connected with priority claim relationship. By performing an experiment with real-world data, we showed that our approach can reveal semantically similar technical terms in other language successfully.

의미 네트워크 모델을 이용한 탐색 용어 선택 시스템의 설계 및 구현에 관한 연구

  • 이효숙
    • Journal of the Korean Society for information Management
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    • v.5 no.1
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    • pp.131-152
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    • 1988
  • It is purposed in this paper to improve the retrieval cffect~venebs through the use of the seman-- t r knowledge of search terms in a computerbased search system. This study is developed it1 three stages include the experimentation of index terms or1 the probab~listir model, indexing with relational operators, and knowledgebase design. The sl~bject experimerltrd is the specific fklds of Chemical Engineering, ' Fluid Flow' and 'Combustion: As for the system ~rnplementatlon. two kinds of search method a r e done. Orie is to search terms related to one specialty word, the other is to retriele the articles based or1 the gueries.

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Optimizing the Additional Term Weight Ratio in Query Expansion Search based on Dictionary Definition (사전 의미 기반의 질의확장 검색에서 추가 용어 가중치 최적화)

  • 최영란;전유정;박순철
    • Journal of Korea Society of Industrial Information Systems
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    • v.8 no.2
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    • pp.45-53
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    • 2003
  • The significances of this paper are of two points. One is that this research develops the query expansion search by adding the related terms based on the dictionary to the original query terms. This method shortens the process of the conventional model of query expansion utilizing the feedback data of the search. The other is that this research tries to find out the optimal point of precisions and recalls by differentiating the weight ratio between original quay and additional terms. This method shows that the efficiency and precision of query expansion search increase.

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Wordnet Extension for IT terminology Using Web Search (웹 검색을 활용한 워드넷에서의 IT 전문 용어 확장)

  • Park, Kyeong-Kook;Lee, Kwang-Mo;Kim, Yu-Seop
    • Annual Conference on Human and Language Technology
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    • 2007.10a
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    • pp.189-193
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    • 2007
  • In this paper, we designed a methodology to expand the WordNet. We added unknown terms like IT technical terms to the existing WordNet by using web search. The WordNet is an online taxonomy representing the relationships among terms, but it usually showed limitation to contain new technical terminologies. That's why we tried to expand the WordNet. Firstly, when we met unregistered terms in WordNet, we built a query of those terms for web search. Given a web search results, we tried to find out terms with a high-level relatedness with the unregistered terms. We used the Korean Morphological Analyzer to score the relatedness between terms and located the unregistered term as a hyponym of terms with high score of relatedness.

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An Example of Systematic Searching for Guidelines to Prevent Catheter-associated Urinary Tract Infections - Part I: Using the PubMed Database (유치도뇨관 감염예방 가이드라인에 관한 체계적 문헌검색 사례 - Part I: PubMed 검색데이터베이스 이용)

  • Kim, Yun-Hee;Jang, Keum-Seong;Chung, Kyung-Hee;Choi, Ja-Yun;Ryu, Se-Ang;Park, Hyunyoung
    • Journal of Korean Academy of Nursing Administration
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    • v.20 no.1
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    • pp.128-143
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    • 2014
  • Purpose: Effective literature searching is essential to support evidence-based nursing. The aim of this study was to present our recent systematic search experience to identify guidelines in PubMed for prevention of catheter-associated urinary tract infections. Methods: Five approaches to the literature search via PubMed were employed. The searches were restricted to items published from 1980 to 2010, for patients admitted to hospital, and in the English language. The search results were compared using the number of records and relevant items, and the sensitivity and precision of each search strategy. Results: The individual approaches retrieved 19-141 of records and 3-6 of relevant items. Sensitivity ranged from 37.5% to 75.0% with the highest values for simple searches and a search combining MeSH terms and free textwords with a methodological search filter. Precision varied from 4.3% to 21.7% and the highest precision was found for MeSH terms with limits feature. Conclusion: The simple search in PubMed is an appropriate way for nurses in a busy clinical practice to search the literature for evidence. However, several approaches using MeSH terms, free textwords, limits feature or methodological search filters are also required to have more efficient and better informed search results.

A Fast Block Matching Algorithm by using the Cross Pattern and Flat-Hexagonal Search Pattern (크로스 패턴과 납작한 육각 탐색패턴을 이용한 고속 블록 정합 알고리즘)

  • 남현우;김종경
    • Journal of the Korea Computer Industry Society
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    • v.4 no.12
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    • pp.953-964
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    • 2003
  • In the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the cross pattern and the flat-hexagon search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the cross pattern, and then lastly finds the other motion vectors that are not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the hexagon-based search algorithm(HEXBS), the proposed cross pattern and flat-hexagonal pattern search algorithm(CFHPS ) improves about 0.2-6.2% in terms of average number of search point per motion vector estimation and improves about 0.02-0.31dB in terms of PSNR(Peak Signal to Noise Ratio).

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Analysis of the Good Job Condition of Which Young People Think and the Impact of Job Search Behavior on Employment (청년들이 생각하는 좋은 일자리 조건과 직업탐색행동이 취업에 미치는 영향 분석)

  • Chang, Wook-hee
    • Journal of Practical Engineering Education
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    • v.13 no.2
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    • pp.351-368
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    • 2021
  • This paper is meaningful in that it empirically studies the good job condition of which young people think and the impact of job search behavior on employment. In addition, employment status and additional job search performance were set as performance variables. The main research results of this study are as follows. First, as for the good job condition considered by young people, wages and salaries in terms of companies, job stability in terms of environment, and work-life balance in terms of individuals were found. Second, job search behavior was found to be a key variable influencing employment status and job search performance. Third, it was found that job-search stress injures employment. Finally, work experience promotes employment and job search performance. Therefore, to increase the employment success rate of young people, above all, various supports for increasing the frequency of young job seekers' active job search behavior are needed. To this end, it suggests that it is necessary to develop a customized youth policy service model and to provide systematic services to meet the needs of young people.

Investment Strategies for KOSPI Index Using Big Data Trends of Financial Market (금융시장의 빅데이터 트렌드를 이용한 주가지수 투자 전략)

  • Shin, Hyun Joon;Ra, Hyunwoo
    • Korean Management Science Review
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    • v.32 no.3
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    • pp.91-103
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    • 2015
  • This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.