• 제목/요약/키워드: Practical Similarity

검색결과 167건 처리시간 0.022초

빌딩 자동화 및 홈 센서 네트워크에서 에너지 효율적이고 실용적인 듀티사이클링 메커니즘 (An Energy-Efficient and Practical Duty-Cycling Mechanism on Building Automation and Home Sensor Networks)

  • 김미희;홍준석
    • 인터넷정보학회논문지
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    • 제13권3호
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    • pp.23-30
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    • 2012
  • 본 논문에서는 이론과 실제 현상의 차이를 보이기 위해 우선 테스트베드 센서 네트워크에서 이론에 기반한 이웃 노드 집합과 실제 연결 설정된 이웃 노드 집합의 차이의 결과를 보인다. 이러한 결과는 이론적 통신 반경에 근거한 관리 메커니즘들(예, 듀티사이클링, 라우팅, 애그리게이션 등)이 의도한 성능을 얻지 못할 가능성을 시사해 준다. 본 논문에서는 에너지 효율성을 고려하여 실제 이웃 노드 집합에 기반한 실용적인 듀티사이클링 메커니즘을 제안한다. 이 메커니즘은 각 존(의도되어 분할된 네트워크의 일부 영역)에서 특정 임계치 내의 유사성을 가진 센싱값들의 중복 전송을 억제한다. 실제 센서 데이터를 이용한 시뮬레이션을 통하여 제안한 메커니즘이 중요 센싱값의 전송을 보장하며, 네트워크 라이프타임을 증가시킴을 보인다.

A practical application of cluster analysis using SPSS

  • Kim, Dae-Hak
    • Journal of the Korean Data and Information Science Society
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    • 제20권6호
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    • pp.1207-1212
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    • 2009
  • Basic objective in cluster analysis is to discover natural groupings of items or variables. In general, clustering is conducted based on some similarity (or dissimilarity) matrix or the original input text data. Various measures of similarities (or dissimilarities) between objects (or variables) are developed. We introduce a real application problem of clustering procedure in SPSS when the distance matrix of the objects (or variables) is only given as an input data. It will be very helpful for the cluster analysis of huge data set which leads the size of the proximity matrix greater than 1000, particularly. Syntax command for matrix input data in SPSS for clustering is given with numerical examples.

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A Post-Analysis of Decision Tree to Detect the Change of Customer Behavior on Internet Shopping Mall

  • Kim, Jae kyeong;Song, Hee-Seok;Kim, Tae-Sung
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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    • pp.456-463
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    • 2001
  • Understanding and adapting to changes of customer behavior in internet shopping mall is an important aspect to survive in continuously changing environment. This paper develops a methodology based on decision tree algorithms to detect changes of customer behavior automatically from customer profiles and sales data at different time snapshots. We first define three types of changes as emerging pattern, unexpected change and the added/perished rule. Then, it is developed similarity and difference measures for rule matching to detect all types of change. Finally, the degree of change is developed to evaluate the amount of change. A Korean internet shopping mall case is evaluated to represent the performance of our methodology. And practical business implications for this methodology are also provided.

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A Clustering Algorithm Considering Structural Relationships of Web Contents

  • Kang Hyuncheol;Han Sang-Tae;Sun Young-Su
    • Communications for Statistical Applications and Methods
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    • 제12권1호
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    • pp.191-197
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    • 2005
  • Application of data mining techniques to the world wide web, referred to as web mining, has been the focus of several recent researches. With the explosive growth of information sources available on the world wide web, it has become increasingly necessary to track and analyze their usage patterns. In this study, we introduce a process of pre-processing and cluster analysis on web log data and suggest a distance measure considering the structural relationships between web contents. Also, we illustrate some real examples of cluster analysis for web log data and look into practical application of web usage mining for eCRM.

온라인 리뷰 수용에 영향을 미치는 요인 : 온라인 리뷰 품질과 동의성을 중심으로 (Determinants of Online Review Adoption : Focusing on Online Review Quality and Consensus)

  • 허성혜;류성렬;전수현
    • Journal of Information Technology Applications and Management
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    • 제16권4호
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    • pp.41-58
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    • 2009
  • This research investigated how people are influenced to adopt online review. We applied the Elaboration Likelihood Model (ELM) and the Technology Acceptance Model (TAM) to this study. Our research model highlights the assessment of online review usefulness as a mediator from online review quality to online review adoption. This research predicted online review consensus has a role to bulid up online reviw usefulness. This study also includes vividness and perceived similarity as determinants of online review quality. Survey data reflect user's perceptions of actual online review they read. Results support most of research hypotheses except hypothesis related to moderating effect of user involvement. This research offers a model for understanding online review user's acceptance. Additional theoretical and practical implications are also discussed in the paper.

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얼굴 방향에 기반을 둔 컴퓨터 화면 응시점 추적 (A Gaze Tracking based on the Head Pose in Computer Monitor)

  • 오승환;이희영
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 하계종합학술대회 논문집(3)
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    • pp.227-230
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    • 2002
  • In this paper we concentrate on overall direction of the gaze based on a head pose for human computer interaction. To decide a gaze direction of user in a image, it is important to pick up facial feature exactly. For this, we binarize the input image and search two eyes and the mouth through the similarity of each block ( aspect ratio, size, and average gray value ) and geometric information of face at the binarized image. We create a imaginary plane on the line made by features of the real face and the pin hole of the camera to decide the head orientation. We call it the virtual facial plane. The position of a virtual facial plane is estimated through projected facial feature on the image plane. We find a gaze direction using the surface normal vector of the virtual facial plane. This study using popular PC camera will contribute practical usage of gaze tracking technology.

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A Methodology for Ontology-based Knowledge Acquisition and Structuring in an Industry-Academic-Government Project ″Go Japan!″

  • Hideki-Mima;Yoon, Tae-Sung
    • 한국전자거래학회:학술대회논문집
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    • 한국전자거래학회 2003년도 종합학술대회 논문집
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    • pp.197-203
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    • 2003
  • The purpose of the study is to develop an integrated knowledge structuring system for the domain of engineering, in which ontology-based literature mining, knowledge acquisition, knowledge integration, and knowledge retrieval are combined using XML-based tag information and ontology management. The system supports combining different types of databases (papers and patents, technologies and innovations) and retrieving different types of knowledge simultaneously. The main objective of the system is to facilitate knowledge acquisition and knowledge retrieval from documents through an ontology-based dynamic similarity calculation and a visualization of automatically structured knowledge. Through experimentations we conducted using 100,000 words economic documents reported in the "Go! Japan" project for analyzing Japanese industrial situation, and 100,000 words molecular biology Papers, we show the system is Practical enough for accelerating knowledge acquisition and knowledge discovery from the information sea.

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Facial Feature Tracking and Head Orientation-based Gaze Tracking

  • Ko, Jong-Gook;Kim, Kyungnam;Park, Seung-Ho;Kim, Jin-Young;Kim, Ki-Jung;Kim, Jung-Nyo
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.11-14
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    • 2000
  • In this paper, we propose a fast and practical head pose estimation scheme fur eye-head controlled human computer interface with non-constrained background. The method we propose uses complete graph matching from thresholded images and the two blocks showing the greatest similarity are selected as eyes, we also locate mouth and nostrils in turn using the eye location information and size information. The average computing time of the image(360*240) is within 0.2(sec) and we employ template matching method using angles between facial features for head pose estimation. It has been tested on several sequential facial images with different illuminating conditions and varied head poses, It returned quite a satisfactory performance in both speed and accuracy.

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A Post-analysis of the Association Rule Mining Applied to Internee Shopping Mall

  • Kim, Jae-Kyeong;Song, Hee-Seok
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2001년도 춘계정기학술대회
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    • pp.253-260
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    • 2001
  • Understanding and adapting to changes of customer behavior is an important aspect for a company to survive in continuously changing environment. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different time snapshots. For this purpose, we first define three types of changes as emerging pattern, unexpected change and the added / perished rule. Then we develop similarity and difference measures for rule matching to detect all types of change. Finally, the degree of change is evaluated to detect significantly changed rules. Our proposed methodology can evaluate degree of changes as well as detect all kinds of change automatically from different time snapshot data. A case study for evaluation and practical business implications for this methodology are also provided.

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Optimized Chinese Pronunciation Prediction by Component-Based Statistical Machine Translation

  • Zhu, Shunle
    • Journal of Information Processing Systems
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    • 제17권1호
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    • pp.203-212
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    • 2021
  • To eliminate ambiguities in the existing methods to simplify Chinese pronunciation learning, we propose a model that can predict the pronunciation of Chinese characters automatically. The proposed model relies on a statistical machine translation (SMT) framework. In particular, we consider the components of Chinese characters as the basic unit and consider the pronunciation prediction as a machine translation procedure (the component sequence as a source sentence, the pronunciation, pinyin, as a target sentence). In addition to traditional features such as the bidirectional word translation and the n-gram language model, we also implement a component similarity feature to overcome some typos during practical use. We incorporate these features into a log-linear model. The experimental results show that our approach significantly outperforms other baseline models.