• Title/Summary/Keyword: QSRF

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An Evaluative Study on the Quality of Papers on the Effects of the Smoking Prevention Programs in Korea

  • Park, Eunok
    • Korean Journal of Health Education and Promotion
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    • v.20 no.4
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    • pp.67-78
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    • 2003
  • This investigation was performed to summarize a few prominent features of smoking prevention program studies and to evaluate the quality of smoking prevention program studies using the Quality of Study Rating Form (QSRF). 24 school-based smoking prevention programs were subjected to an evaluation of study quality using QSRF. Study quality was 57.29 points out of 100 points on average, so it cannot be said that study quality was good. Most of the studies described the subjects and the intervention contents and intervention time. 50% stated where the intervention occurred specifically, 50% of the studies either discussed a specific theory that justified the use of one or more intervention methods, or they cited literature said to support the chosen intervention method. Only one study assigned subjects randomly to experimental groups or control groups and 50.0% of the studies showed baseline equality. There was no study where subjects were blind to being in the treatment or control group or where subjects were selected randomly by random sampling procedure. 79.2% of the studies had non-treated control groups and 20.8% of the studies had comparison groups with other treatments in the form of either other delivery methods or other contents. Sample sizes were larger than 21 in the experimental group for all studies. 75% of the studies stated face validity of outcome measure or cited from previous literature. 58.3% of the studies tested reliability and 45.8% reported the reliability measure was a figure of .70 or greater. There was no study where those rating outcomes were rated blind, because researchers generally collected data by themselves. Outcome measures were taken only after the intervention was completed and tests of statistical significance were generally referred to statistical method and p value in all studies. All studies met the criteria that follow-up was greater than 75%. The implications for the future studies were discussed.

A Study on Document Retrieval of Web Using Relevance Feedback (적합성 피드백을 이용한 웹 문서검색에 관한 연구)

  • 김영천;이성주
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.3
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    • pp.597-604
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    • 2001
  • In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.

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A Study on Information Retrieval Using Query Splitting Relevance Feedback (질의분해 적합성 피드백을 이용한 정보검색에 관한 연구)

  • 김영천;박병권;이성주
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.3
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    • pp.252-257
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    • 2001
  • In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.

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A Study on Improving the Effectiveness of Retrieval System Using Query Splitting Relevance Feedback (질의분해 적합성 피드백을 이용한 검색시스템의 성능 증진에 관한 연구)

  • 김영천;박병권;이성주
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.231-235
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    • 2001
  • 순수한 부울 검색 시스템은 문서와 질의 사이의 유사도를 나타내는 문서값을 계산할 수 없기 때문에, 검색된 문서들을 질의를 만족하는 정보에 따라 정렬할 수 없다. 부울 검색 시스템의 이러한 단점을 보완하는 방법으로 MMM 모델, Paice 모델, P-norm 모델이 개발되었다. 본 논문에서는 높은 검색 효과를 제공하는 질의분해 적합성 피드백(QSRF) 모델을 제안한다. 질의 분해 적합성 피드백 모델의 연산 특성이 MMM, Paice, P-norm 모델보다 우수함을 설명하고, 또한 성능 비교를 통하여 이를 입증한다.

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