• Title/Summary/Keyword: Text-type Index

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A Study on the Extraction and Utilization of Index from Bibliographic MARC Database (서지마크 데이터베이스로부터의 색인어 추출과 색인어의 검색 활용에 관한 연구 - 경북대학교 도서관 학술정보시스템 사례를 중심으로 -)

  • Park Mi-Sung
    • Journal of Korean Library and Information Science Society
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    • v.36 no.2
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    • pp.327-348
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    • 2005
  • The purpose of this study is to emphasize the importance of index definition and to prepare the basis of optimal index in bibliographic retrieval system. For the purpose, this research studied a index extraction theory on index tag definition and index normalization from the bibliographic marc database and analyzed a retrieval utilization rate of extracted index. In this experiment, we divided index between text-type and code-type about the generated 29,219,853 indexes from 2,200,488 bibliographic records and analyzed utilization rate by the comparison of index-type and index term of web logs. According to the result, the text-type indexes such as title, author, publication, subject are showed high utilization rate while the code-type indexes were showed low utilization rate. So this study suggests that the unused index is removed from index definition to optimize index.

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A Study on Classifications of Useful Customer Reviews by Applying Text Mining Approach (텍스트 마이닝을 활용한 고객 리뷰의 유용성 지수 개선에 관한 연구)

  • Lee, Hong Joo
    • Journal of Information Technology Services
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    • v.14 no.4
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    • pp.159-169
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    • 2015
  • Customer reviews are one of the important sources for purchase decision makings in online stores. Online stores have tried to provide useful reviews in product pages to customers. To assess the usefulness of customer reviews before other users have voted enough on the reviews, diverse aspects of reviews were utilized in prevous studies. Style and semantic information were utilized in many studies. This study aims to test diverse alogrithms and datasets for identifying a proper classification method and threshold to classify useful reviews. In particular, most researches utilized ratio type helpfulness index as Amazon.com used. However, there is another type of usefulness index utilized in TripAdviser.com or Yelp.com, count type helpfulness index. There was no proper threshold to classify useful reviews yet for count type helpfulness index. This study used reivews and their usefulness votes on restaurnats from Yelp.com to devise diverse datasets and applied text mining approaches to classify useful reviews. Random Forest, SVM, and GLMNET showed the greater values of accuracy than other approaches.

- For the Development of Inquiring, integrated Science Curricular Materials - The Comparison and Analysis of Inquiry Activity between "The FAST Program" and "The Secondary Science Books" (탐구적 통합 과학 교재 개발을 위한, "FAST program"과 "중등 과학 교과서"의 탐구 활동 비교 분석)

  • Son, Yeon-A;Lee, Hack-Dong
    • Journal of The Korean Association For Science Education
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    • v.14 no.1
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    • pp.45-57
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    • 1994
  • The purpose of this study is to verify whether the FAST program is the Inquiry Science Curricular Materials, through the Comparison and Analysis of Inquiry Activities between the FAST program and our Secondary Science Books. The results of this study are as follows ; 1. FAST has 226 tasks of the Inquiry Activities, which is analyzed over two times than our text. 2. In level one, FAST holds the parts of Synthesizing Results and Evaluation, Hypothesizing and Designing an Experiment but u.ese aren't found in our text. 3. In level two, our text is analyzed No Discussion 72.2%, Demonstrating or Verifying the Content of the Text 82%, but FAST has Discussion Guided 81.8%, and isn't found any tesk of Demonstrating or Verifying the Content of the text. 4. In level three, our text is exposed a typical type I and analyzed Inquiry Index 15-25 ( Middle ), but FAST is found type IV, excepting Manipulating Apparatus and Observation and analyzed Inquiry Index over 35 ( Very - High ). Therefore, FAST Program is proved to be the desirable Inquiry Science Curricular Materials. In future, this worker is to arrange the results of the following paper as follows ; 1. The verification of the FAST Program by means of the Integrated Science Curricular Materials. 2. The development of the Inquiring, Integrated Science Curricular Materials through the results of the preceding study.

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A New Method Calculating Total Slip of Fault with Fault Separation (단층변위를 이용한 단층의 총 이동량 계산법)

  • Hwang, Jae Ha
    • Economic and Environmental Geology
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    • v.31 no.6
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    • pp.547-555
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    • 1998
  • A new trigonometrical method for calculating total slip (T) of faulting is presented. The parameters for the calculations are used rake of fault striation, strike and dip of fault and of index planar structure such as bedding plane. The faults are groupped into three types. The direction of plunging of fault striation is out of a range ${\pm}90^{\circ}$ to the bedding dip direction in $360^{\circ}$ system, which is groupped into the type I. Meanwhile, the case of the direction lies in the above range can be separated into two different types, type II and type III, according to relative largeness of the angles rake of fault striation and i (see text). The type II has smaller rake than angle i and the type III has larger rake than angle i. Here I propose a few equations for calculating not only total slip (T) but strike slip (L) or dip slip (S) of the faulting. The equations are adapted selectively to the types of fault mentioned before. The limitation of the method is that the equations do not fit to polyphase faulting.

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Analysis of Research Trends on Archival Information Services Using Text Mining (텍스트마이닝을 활용한 국내외 기록서비스 연구동향 분석)

  • Seohee Park;Hye-Eun Lee
    • Journal of Korean Society of Archives and Records Management
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    • v.24 no.1
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    • pp.89-109
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    • 2024
  • The study analyzed the research trends of domestic and international record information services from 2003 to 2022. A total of 136 academic papers registered in the Korea Citation Index (KCI) and 74 from the Library, Information Science & Technology Abstracts (LISTA) were examined by quantitative and qualitative content analysis to understand the research status of 20 years from various angles, such as publication year, research type, researcher type, subject, and purpose. Frequency analysis, co-occurrence frequency analysis, centrality analysis, and topic modeling were performed by applying text mining techniques. Results showed that domestic papers demonstrated a research flow focused on specific institutions or records, and user-centered satisfaction surveys and content-centered studies were conducted. Moreover, foreign papers confirmed various evaluation-oriented and information provision studies, such as data, resources, and collections, along with the research trend focusing on the relationship between archivists and users. The management of information resources was identified as a common topic in both domestic and foreign papers, but it is possible to identify that domestic research focuses on maintaining the quality of domestic information resources, while foreign research focuses on the storage and retrieval of information.

Stock-Index Invest Model Using News Big Data Opinion Mining (뉴스와 주가 : 빅데이터 감성분석을 통한 지능형 투자의사결정모형)

  • Kim, Yoo-Sin;Kim, Nam-Gyu;Jeong, Seung-Ryul
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.143-156
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    • 2012
  • People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

A Text Processing Method for Devanagari Scripts in Andriod (안드로이드에서 힌디어 텍스트 처리 방법)

  • Kim, Jae-Hyeok;Maeng, Seung-Ryol
    • The Journal of the Korea Contents Association
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    • v.11 no.12
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    • pp.560-569
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    • 2011
  • In this paper, we propose a text processing method for Hindi characters, Devanagari scripts, in the Android. The key points of the text processing are to device automata, which define the combining rules of alphabets into a set of syllables, and to implement a font rendering engine, which retrieves and displays the glyph images corresponding to specific characters. In general, an automaton depends on the type and the number of characters. For the soft-keyboard, we designed the automata with 14 consonants and 34 vowels based on Unicode. Finally, a combined syllable is converted into a glyph index using the mapping table, used as a handle to load its glyph image. According to the multi-lingual framework of Freetype font engine, Dvanagari scripts can be supported in the system level by appending the implementation of our method to the font engine as the Hindi module. The proposed method is verified through a simple message system.

Trend Analysis of the Agricultural Industry Based on Text Analytics

  • Choi, Solsaem;Kim, Junhwan;Nam, Seungju
    • Agribusiness and Information Management
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    • v.11 no.1
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    • pp.1-9
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    • 2019
  • This research intends to propose the methodology for analyzing the current trends of agriculture, which directly connects to the survival of the nation, and through this methodology, identify the agricultural trend of Korea. Based on the relationship between three types of data - policy reports, academic articles, and news articles - the research deducts the major issues stored by each data through LDA, the representative topic modeling method. By comparing and analyzing the LDA results deducted from each data source, this study intends to identify the implications regarding the current agricultural trends of Korea. This methodology can be utilized in analyzing industrial trends other than agricultural ones. To go on further, it can also be used as a basic resource for contemplation on potential areas in the future through insight on the current situation. database of the profitability of a total of 180 crop types by analyzing Rural Development Administration's survey of agricultural products income of 115 crop types, small land profitability index survey of 53 crop types, and Statistics Korea's survey of production costs of 12 crop types. Furthermore, this research presents the result and developmental process of a web-based crop introduction decision support system that provides overseas cases of new crop introduction support programs, as well as databases of outstanding business success cases of each crop type researched by agricultural institutions.

A Comparative Study on the Types and its Importance of Trade Claims between China and the United States: Using Text Mining Techniques (중국과 미국의 무역클레임 유형과 중요도 비교 연구 : 텍스트 마이닝 기법을 활용하여)

  • Cheon Yu;Yun-Seop Hwang
    • Korea Trade Review
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    • v.47 no.3
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    • pp.177-190
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    • 2022
  • This study is designed to identify the differences in the types and importance of trade claims at the national level. For analysis data, abstracts of arbitration and court judgments published on the website of the United Nations Commission on International Trade Law are collected and used. The target countries are China and the United States, with 102 cases from China and 59 cases from the United States. By applying topic modeling techniques to the collection decisions of China and the United States, trade claims are categorized, and the importance of each type is identified using the network centrality index derived through semantic network analysis. The analysis results are as follows. First, the main types of trade claims were the same for both the United States and China: product nonconformity, delivery issues, and payments. However, in China, the order of product nonconformity > delivery issues > payments was important, and in the United States, payments > product nonconformity > delivery issues were found to be important. This study is significant in that it presents a strategic trade claim management plan using a quantitative methodology.

Study on Model Case of Ideal Digitization of Korean Ancient Books (국학고전자료의 디지털화를 위한 모범적인 방안 연구)

  • Lee, Hee-Jae
    • Journal of the Korean Society for information Management
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    • v.22 no.1 s.55
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    • pp.105-123
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    • 2005
  • The most of all, this study is planned to search an ideal methods to develop the digital library system for our korean ancient books for their safe preservation and, at the same time, for their perusal of transcendental time and space : first. to offer the various access points like traditional oriental Four parts Classics classification, current subject classification and index keyword, etc. : second, to program a digital library system using MARC or XML, but with all bibliographic descriptive elements as possible; third, to prepare the more easy annotated bibliography and index for users' better comprehension, and last, to build original text database for practical reading to avoid the damage of original text. This type of korean ancient books digital library will be developed to the real international bibliographic control by networking enter the same kinds of internal and external organizations.