• Title/Summary/Keyword: Known-Item Search

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Known-Item Retrieval Performance of a PICO-based Medical Question Answering Engine

  • Vong, Wan-Tze;Then, Patrick Hang Hui
    • Asia pacific journal of information systems
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    • v.25 no.4
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    • pp.686-711
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    • 2015
  • The performance of a novel medical question-answering engine called CliniCluster and existing search engines, such as CQA-1.0, Google, and Google Scholar, was evaluated using known-item searching. Known-item searching is a document that has been critically appraised to be highly relevant to a therapy question. Results show that, using CliniCluster, known-items were retrieved on average at rank 2 ($MRR@10{\approx}0.50$), and most of the known-items could be identified from the top-10 document lists. In response to ill-defined questions, the known-items were ranked lower by CliniCluster and CQA-1.0, whereas for Google and Google Scholar, significant difference in ranking was not found between well- and ill-defined questions. Less than 40% of the known-items could be identified from the top-10 documents retrieved by CQA-1.0, Google, and Google Scholar. An analysis of the top-ranked documents by strength of evidence revealed that CliniCluster outperformed other search engines by providing a higher number of recent publications with the highest study design. In conclusion, the overall results support the use of CliniCluster in answering therapy questions by ranking highly relevant documents in the top positions of the search results.

온라인열람목록의 탐색유형과 탐색성과에 관한 분석-국립중앙도서관 이용자를 대상으로 -

  • 장혜란;석경임
    • Journal of Korean Library and Information Science Society
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    • v.22
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    • pp.139-169
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    • 1995
  • The purpose of this study is to analyze the search pattern and search outcome of the National Central Library OPAC users by measuring their success rates and identifying the factors of failure and the personal background which bring about the differences of the search outcome. Various methods have been used for the study. Personal interview was used to find the pattern of the search, observation method was used to investigate the search process and the failure factors, and a questionnaire was used to survey personal background of searchers. The data were collected during the period of 7 days from April 17, 1995 through April 23, 1995. The search of 1, 217 cases, sampling systematically 25% out of the whole users, were collected and analyzed for the study. The findings of the study can be summarized as follows : First, in regard to the pattern, known-item search(72.6%) was preferred to the subject search(27.4%) and in case of known-item search the access point used were in the order of title, author, title and author. Second, the overall success rate of known-item search was 50.3% and the success rates were in order of author and date, title, and author. The failure factors of known-item search were divided into users factor of 67% and the database factor of 33%, respectively. Third, in case of subject search, its overall success rate was 44.1% and the keyword was the major access point, and the average of precision ratio was very low. Fourth, the analysis of the personal background related to the search outcome has shown significant differences by sex, the experience of using OPAC, education level, and the frequency of using other information retrieval systems. Based on the results the following suggestions can be made to improve the search outcome : First, the system should be su n.0, pplemented online help function to assist users to overcome the failure during search. Second, user instruction in group or individual should be implemented for the users to understand the system.

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The Relationship between Internet Search Volumes and Stock Price Changes: An Empirical Study on KOSDAQ Market (개별 기업에 대한 인터넷 검색량과 주가변동성의 관계: 국내 코스닥시장에서의 산업별 실증분석)

  • Jeon, Saemi;Chung, Yeojin;Lee, Dongyoup
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.81-96
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    • 2016
  • As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

Online Catalog Use Study in a University Library (대학도서관의 온라인목록 이용특성에 관한 연구 -덕성여자대학교를 중심으로-)

  • Yoo Jae-Ok
    • Journal of the Korean Society for Library and Information Science
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    • v.31 no.4
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    • pp.289-318
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    • 1997
  • The purpose of this study is to identify users behavioral characteristics for using the online catalog opened in May 1996 at Duksung Women's University Library. 278 student users were surveyed from October 4th to 8th in 1996. Major findings are as follows. 1. Most users$(87.4\%)$ prefer the online catalog to the card catalog and regard the online catalog easy to use$(89.6\%)$ 2. $(65.8\%)$ of users are active users who frequently use the online catalog at least 10 times or more per semester. 3. $10.4\%$ of users feel the online catalog difficult because they do not know how to use it. 4. Most users prefer the menu search mode among menu, command and fill-in-blank search modes offered by DISCOVER. The most preferred access points are the title for known-item search and subject headings for subject search. 5. User's attitude toward the online catalog is very favorable$(83.5\%)$, however, the search success rate is rather low $(77.0\%)$ compared to that of the card catalog $(87.0\%)$ 6. The title and author are regarded easy to use among access points offered by DISCOVER. Classification numbers and call numbers are the least easy access points to use. 7. Since users show lack of knowledge of how to use the online catalog, education and training programs on the online catalog use for users are needed. 8. Users showed different search patterns for pursuing different search goals. The most preferred access points are the title for known-item search and subject headings for subject search. These search behaviors are different from those in using the card for both the known-item search and subject search was the title.

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Evaluating and Comparing the Search & Discovery Features: Focusing on the Public Libraries OPACs and the Internet Bookstores (탐색과 디스커버리 기능 평가 연구 - 공공도서관 OPAC과 인터넷 서점을 중심으로 -)

  • Han, Seunghee
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.1
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    • pp.493-511
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    • 2016
  • Discovery is an emerging concept to enhance the search capabilities of library resources with the Next Generation Library Catalog. This paper defined the Discovery feature based on the information search behavior, and then derived the elements that make up its function. After that, the 11 regional representatives libraries' OPACs and 3 Internet bookstores are evaluated and compared against Search & Discovery capabilities. As a result, the Internet bookstores were superior to the libraries' OPACs for all the elements that make up the Discovery functions. This study verified that the public libraries OPACs are still concentrating on known item search, and it is hard for the users to meet a serendipity which is gained through the Discovery functions.

A Heuristic Algorithm for the Two-Dimensional Bin Packing Problem Using a Fitness Function (적합성 함수를 이용한 2차원 저장소 적재 문제의 휴리스틱 알고리즘)

  • Yon, Yong-Ho;Lee, Sun-Young;Lee, Jong-Yun
    • The KIPS Transactions:PartB
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    • v.16B no.5
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    • pp.403-410
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    • 2009
  • The two-dimensional bin packing problem(2D-BPP) has been known to be NP-hard, and it is difficult to solve the problem exactly. Many approximation methods, such as genetic algorithm, simulated annealing and tabu search etc, have been also proposed to gain better solutions. However, the existing approximation algorithms, such as branch-and-bound and tabu search, have shown the low efficiency and the long execution time due to a large of iterations. To solve these problems, we first define the fitness function to simplify and increase the utility of algorithm. The function decides whether an item is packed into a given area, and as an important information for a packing strategy, the number of subarea that can accommodate a given item is obtained from the variant of the fitness function. Then we present a heuristic algorithm BF for 2D bin packing, constructed by the fitness function and subarea. Finally, the effectiveness of the proposed algorithm will be expressed by the comparison experiments with the heuristic and the metaheuristic of the literatures. As comparing with existing heuristic algorithms and metaheuristic algorithms, it has been found that the packing rate of algorithm BP is the same as 97% as existing heuristic algorithms, FFF and FBS, or better than them. Also, it has been shown the same as 86% as tabu search algorithm or better.

Catalog use study : with reference to universities in Daegu (대학도서관의 목록이용연구)

  • 최달현
    • Journal of Korean Library and Information Science Society
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    • v.9
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    • pp.241-266
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    • 1982
  • This paper gives a summary and overview of a survey conducted at the catalogues of five universities in Daegu during November 1982. The major objective of this study was to secure information about user needs in order to improve the catalogue in Korean university libraries. Data was collected by a combined method of questionnaire and interview. A total of 379 respondents were taken on a randomly selected sample of catalogue users. Results of the survey can be summarized as follows: 1. Eighty-eight percent of the students answered that they had used the library more than twice a month. Nevertheless the number of students consulting the catalogue with the same frequency was only 220, or a n.0, pproximately 58 percent. Those who used the library most tended to use the catalogue more than those who rarely came to the library. 2. Those who had been shown how to use their own catalogue were only 32.5percent of which the students found the instruction sufficient for them to be able to use the catalogue were only 37.5 percent. In particular, they stated that instructions by printed materials and/or library orientation were so poor that they didn't give much help in using the catalogue. This problem makes many libraries to review their own method of instruction in order to encourage patrons to use the catalogue more effectively. 3. Most of the students consulted the catalogue in order to locate library materials. Known-item searches and subject searches were 84 and 16 percent respectively. While 70.5 percent of the students used the author-title catalogue without any difficulties, only 35.5 percent of those stated that using the classed catalogue was easy. 4. It was surprising that the number of students using title access in the search was far greater than that of students using author access. In contrast with this, other studies conducted by many earlier overseas investigators revealed that the great majority of patrons tended to use the latter first. Therefore, we should put more emphasis on the title entries in the catalogue itself as well as cataloging rules. 5. Most useful bibliographic elements in the entry were author, title, call number, date and publisher whereas edition, series statement and the location of publisher were rarely used compared with the other elements. Content note was the most desirable element in the entry to be involved, for many catalogers were used not to describe it on the note area. 6. The chief reason given for not using the catalogue was "I can manage without it" with "It's difficult to understand contents of the card entry." The other one was "It's useless to search materials by the catalogue because I've failed so many times to obtain them out of the stock." In response to this, circulation and acquisition system should be improved not to make such complaints any more.

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Fermentation of Cucurbita maxima Extracts with Microganisms from Kimchi (김치 유래 유산균을 이용한 단호박 발효음료 제조 기술 개발)

  • Roh, Hyun-Ji;Kim, Gi-Eun
    • KSBB Journal
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    • v.24 no.2
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    • pp.149-155
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    • 2009
  • 19 strains, which could be identified as Lactobacillus sp. were isolated. The Cucurbita maxima has been known as a traditional healthy food and variable positive effects on the human body were already reported. In this study we tried to develop a production process for a healthy fermented drink with Cucurbita maxima and strains originated from Kimchi. Many kinds of lacctobacci species existed in the fermented food cannot survive in the acidic conditions in the stomach. So we tried to search and select a strain, which can arrive to the small intestine. A species of a Lactobacillus named as C332 was identifed as Lactobacillus plantarum and selected for the fermentation process. With the treatment with artificial gastric juice and artificial bile the survival rate of the cells could be calculated. The physiological characteristics at the variable conditions have been tested. After fermentation process the sensoric tests on the product with panels were tried. The most of the cells could survive in the acidic conditions and falcultive anaerobe. Especially some antibacterial effects aganinst E.coli were also found. With all kinds of the results from our research the fermented Cucurbita maxima drink can be a successful item in the market.

Resolving the 'Gray sheep' Problem Using Social Network Analysis (SNA) in Collaborative Filtering (CF) Recommender Systems (소셜 네트워크 분석 기법을 활용한 협업필터링의 특이취향 사용자(Gray Sheep) 문제 해결)

  • Kim, Minsung;Im, Il
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.137-148
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    • 2014
  • Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used

    . Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.

  • Trend and Further Research of Rice Quality Evaluation (쌀의 품질평가 현황과 금후 연구방향)

    • Son, Jong-Rok;Kim, Jae-Hyun;Lee, Jung-Il;Youn, Young-Hwan;Kim, Jae-Kyu;Hwang, Hung-Goo;Moon, Hun-Pal
      • KOREAN JOURNAL OF CROP SCIENCE
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      • v.47
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      • pp.33-54
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      • 2002
    • Rice quality is much dependent on the pre-and post harvest management. There are many parameters which influence rice or cooked rice qualitys such as cultivars, climate, soil, harvest time, drying, milling, storage, safety, nutritive value, taste, marketing, eating, cooking conditions, and each nations' food culture. Thus, vice evaluation might not be carried out by only some parameters. Physicochemical evaluation of rice deals with amy-lose content, gelatinizing property, and its relation with taste. The amylose content of good vice in Korea is defined at 17 to 20%. Other parameters considered are as follows; ratio of protein body-1 per total protein amount in relation to taste, and oleic/linoleic acid ratio in relation to storage safety. The rice higher Mg/K ratio is considered as high quality. The optimum value is over 1.5 to 1.6. It was reported that the contents of oligosaccharide, glutamic acid or its derivatives and its proportionalities have high corelation with the taste of rice. Major aromatic compounds in rice have been known as hexanal, acetone, pentanal, butanal, octanal, and heptanal. Recently, it was found that muco-polysaccharides are solubilized during cooking. Cooked rice surface is coated by the muco-polysaccharide. The muco-polysaccharide aye contributing to the consistency and collecting free amino acids and vitamins. Thus, these parameters might be regarded as important items for quality and taste evaluation of rice. Ingredients of rice related with the taste are not confined to the total rice grain. In the internal kernel, starch is main component but nitrogen and mineral compounds are localized at the external kernel. The ingredients related with taste are contained in 91 to 86% part of the outside kernel. For safety that is considered an important evaluation item of rice quality, each residual tolerance limit for agricultural chemicals must be adopted in our country. During drying, rice quality can decline by the reasons of high drying temperature, overdrying, and rapid drying. These result in cracked grain or decolored kernel. Intrinsic enzymes react partially during the rice storage. Because of these enzymes, starch, lipid, or protein can be slowly degraded, resulting in the decline of appearance quality, occurrence of aging aroma, and increased hardness of cooked rice. Milling conditions concerned with quality are paddy quality, milling method, and milling machines. To produce high quality rice, head rice must contain over three fourths of the normal rice kernels, and broken, damaged, colored, and immature kernels must be eliminated. In addition to milling equipment, color sorter and length grader must be installed for the production of such rice. Head rice was examined using the 45 brand rices circulating in Korea, Japan, America, Australia, and China. It was found that the head rice rate of brand rice in our country was approximately 57.4% and 80-86% in foreign countries. In order to develop a rice quality evaluation system, evaluation of technics must be further developed : more detailed measure of qualities, search for taste-related components, creation and grade classification of quality evaluation factors at each management stage of treatment after harvest, evaluation of rice as food material as well as for rice cooking, and method development for simple evaluation and establishment of equation for palatability. On policy concerns, the following must be conducted : development of price discrimination in conformity to rice cultivar and grade under the basis of quality evaluation method, fixation of head rice branding, and introduction of low temperature circulation.


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