• 제목/요약/키워드: Text box

검색결과 71건 처리시간 0.041초

Analyzing Box-Office Hit Factors Using Big Data: Focusing on Korean Films for the Last 5 Years

  • Hwang, Youngmee;Kim, Kwangsun;Kwon, Ohyoung;Moon, Ilyoung;Shin, Gangho;Ham, Jongho;Park, Jintae
    • Journal of information and communication convergence engineering
    • /
    • 제15권4호
    • /
    • pp.217-226
    • /
    • 2017
  • Korea has the tenth largest film industry in the world; however, detailed analyses using the factors contributing to successful film commercialization have not been approached. Using big data, this paper analyzed both internal and external factors (including genre, release date, rating, and number of screenings) that contributed to the commercial success of Korea's top 10 ranking films in 2011-2015. The authors developed a WebCrawler to collect text data about each movie, implemented a Hadoop system for data storage, and classified the data using Map Reduce method. The results showed that the characteristic of "release date," followed closely by "rating" and "genre" were the most influential factors of success in the Korean film industry. The analysis in this study is considered groundwork for the development of software that can predict box-office performance.

E-business 웹사이트에서의 데이터 입력디자인에 관한 비교 연구 (A Comparative Study on Data Input Design of E-business Websites)

  • 정홍인
    • 디자인학연구
    • /
    • 제17권1호
    • /
    • pp.127-134
    • /
    • 2004
  • 본 연구를 통해 e-business 웹사이트에서 사용자의 입력에 사용되는 어느 정도 표준화된 인터페이스 디자인들을 실험을 통해 비교하고 최적의 사용법을 알아내었다. 풀다운 메뉴, 텍스트 입력 창, 리스트, 라디오 버튼 등의 입력 디자인(도구)들이 실험에 사용되었으며 이들은 호텔 객실의 예약 웹사이트 시뮬레이션을 통해 비교되었다. 실험 결과 사용자의 입력 선택 사양이 4가지 이상인 경우 전문가에겐 텍스트 입력 창이 입력시간을 줄여주고 일반 사용자에게는 풀다운 메뉴가 사용성 측면에서 효율적임을 알 수 있었다. 단지 두 가지의 선택 사양이 존재할 경우엔 만족도, 유연성, 단순성을 고려했을 땐 리스트가 우수하며 사용 편의성 면에선 라디오 버튼이 최적의 인터페이스로 나타났다. 연구 결과를 사용자의 데이터 입력이 필요한 인터렉티브한 웹사이트의 디자인에 적용할 경우 경제적 효율과 사용성을 증대시킬 것이다.

  • PDF

데카르트의 심신론이 의학에 미친 영향 (The impact of Rene Descartes′s Mind-Body Theory on Medicin)

  • 반덕진
    • 보건행정학회지
    • /
    • 제10권1호
    • /
    • pp.31-56
    • /
    • 2000
  • A purpose of this study is to study on Rene Descartes's mind-body theory in medical aspect. Though Rene Descartes was not so much a doctor as a philosopher, he had health and medical science at heart. When he came into the world in 1596, he was in poor health. Therefore, he suffered from his bad health. Descartes's ideas absolutely colored Western thought for three hundred years, especially, his mind-body theory, mechanistic life-view, and reductionism had important effect on medical study and science of public health. As a rule, we know that his mind-body theory was applicable to mind-body dualism, and his mind-body dualism was connected with biomedical model of medicine. But by this study, his mind-body theory was not only mind-body dualism but also mind-body monoism. And he asserted mind-body interaction too. In other words, he advocated mind-body dualism in scientific aspect, but he knew mind-body monoism from his experence. He confessed this fact to Princess Elizabeth of Bohemia, he wrote mind-body interaction in $\boxDr$Discours de la methode$\boxUl$, $\boxDr$Meditationes de prima philosophia$\boxUl$, and $\boxDr$Traite des passions de 1'ame$\boxUl$ etc. However, only mind-body dualism of his mind-body theories was written in our medical text book, morever mental realm was excluded from the persuit of learning Descartes advocated a mechanistic world-view and mechanistic life-view, he regarded human body as a machine part. And a paticent corresponds to a troubled machine, a doctor deserves a repairman. But this point of view made holistic understanding of man impossible. Descartes divide the whole into basic building blocks, we named the approach Reductionism. Reductionism led to ontological concept in medical science, bacteriology established 'specific cause-specific disease-specific therapy'. We examined medical influence of Descartes's thought, we need to draw out a philosophic basis of medical science and science of public health by a close study of his records.

  • PDF

엑셀 매크로기능을 이용한 DES 암호화 교육도구 개발 (On the development of DES encryption based on Excel Macro)

  • 김대학
    • Journal of the Korean Data and Information Science Society
    • /
    • 제25권6호
    • /
    • pp.1419-1429
    • /
    • 2014
  • 본 논문에서는 1977년 미국 국립기술표준원이 FIPS (연방정보처리기준; federal information processing standard) 46으로 공표한 암호화 표준인 현대 대칭키 블록 암호 DES (data encryption standard)의 암호화 전 과정에 대하여 엑셀 매크로 기능을 활용하여 암호화와 복호화에 사용할 수 있는 매크로를 개발하였다. 평문과 암호문과의 관계를 숨기는 확산과 암호문과 암호 키 사이의 관계를 숨기는 혼돈을 반복하는 라운드는 DES 구조의 핵심이다. 평문을 암호화 하는 DES 구조를 살펴보고 엑셀 매크로기능을 이용하여 암호화를 완성하는 매크로의 구현을 제안하고 개발된 매크로의 정확성과 활용성을 서술하였다.

An Optimized e-Lecture Video Search and Indexing framework

  • Medida, Lakshmi Haritha;Ramani, Kasarapu
    • International Journal of Computer Science & Network Security
    • /
    • 제21권8호
    • /
    • pp.87-96
    • /
    • 2021
  • The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

Big Data Smoothing and Outlier Removal for Patent Big Data Analysis

  • Choi, JunHyeog;Jun, Sunghae
    • 한국컴퓨터정보학회논문지
    • /
    • 제21권8호
    • /
    • pp.77-84
    • /
    • 2016
  • In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

정규화 용어빈도가중치에 의한 자동문서분류 (Automatic Text Categorization by using Normalized Term Frequency Weighting)

  • 김수진;김민수;백장선;박혁로
    • 한국정보과학회:학술대회논문집
    • /
    • 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
    • /
    • pp.510-512
    • /
    • 2003
  • 본 논문에서는 문서의 자동 분류를 위한 용어 빈도 가중치 계산 방법으로 Box-Cox변환기법을 응용한 정규화 용어빈도 가중치를 정의하고, 이를 문서 분류에 적응하였다. 여기서 Box-Cox 변환기법이란 자료를 정규분포화 할 때 적용하는 통계적인 변환방법으로서, 본 논문에서는 이를 응용하여 새로운 용어빈도가중치 계산법을 제안한다. 문서에서 등장한 용어 빈도는 너무 많거나 적게 등장할 경우, 중요도가 떨어지게 되는데, 이는 용어의 중요도가 빈도에 따른 정규분포로 모델링 될 수 있다는 것을 의미한다. 또한 정규화 가중치 계산방법은 기존의 용어빈도 가중치 공식과 비교할 때, 용어마다 계산방법이 달라져, 로그나 루트와 같은 고정된 가중치 방법보다는 좀더 일반적인 방법이라 할 수 있다. 신문기사 8000건을 대상으로 4개의 그룹으로 나누어 실험 한 결과, 정규화 용어빈도가중치 계산방법이 모두 우위의 분류 정확도롤 가져, 본 논문에서 제안한 방법이 타당함을 알 수 있다.

  • PDF