• Title/Summary/Keyword: Information Models

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A Comparative Study on Models of Information Seeking Behavior (정보추구행태모형의 비교 연구)

  • 사공복희
    • Journal of the Korean Society for information Management
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    • v.20 no.1
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    • pp.93-119
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    • 2003
  • Models of Information seeking behavior were reviewed and analyzed. General models which could be utilized in designing empirical research of information seeking behavior were suggested. On general models of information seeking, applicable in multiple contexts. occupations, roles, and knowledge domains were focused. The models by Wilson. Krikelas. Dervin, Ellis. Kuhlthau, Leckie, and Johnson were examined chronologically.

Scalable Prediction Models for Airbnb Listing in Spark Big Data Cluster using GPU-accelerated RAPIDS

  • Muralidharan, Samyuktha;Yadav, Savita;Huh, Jungwoo;Lee, Sanghoon;Woo, Jongwook
    • Journal of information and communication convergence engineering
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    • v.20 no.2
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    • pp.96-102
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    • 2022
  • We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.

A Note on Performance of Conditional Akaike Information Criteria in Linear Mixed Models

  • Lee, Yonghee
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.507-518
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    • 2015
  • It is not easy to select a linear mixed model since the main interest for model building could be different and the number of parameters in the model could not be clearly defined. In this paper, performance of conditional Akaike Information Criteria and its bias-corrected version are compared with marginal Bayesian and Akaike Information Criteria through a simulation study. The results from the simulation study indicate that bias-corrected conditional Akaike Information Criteria shows promising performance when candidate models exclude large models containing the true model, but bias-corrected one prefers over-parametrized models more intensively when a set of candidate models increases. Marginal Bayesian and Akaike Information Criteria also have some difficulty to select the true model when the design for random effects is nested.

A Survey on Information Economics and Models (정보경제학과 모텔에 관한 고찰)

  • 윤구호
    • Journal of Korean Library and Information Science Society
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    • v.32 no.2
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    • pp.121-144
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    • 2001
  • The origins, definition and research area of information economics are outlined in brief. For the better understanding and discussion of information economics, some important concept that require examination, such as information economy, resources, uncertainty and information value are reviewed in detail. Furthermore, a brief history of model and issues surrounding models are examined. In particular, some applications of models related to social sciences have been investigated since these models hold tremendous potential as diagnostic and test tools in the practical and theoretical work of library and information science.

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Forecasting value-at-risk by encompassing CAViaR models via information criteria

  • Lee, Sangyeol;Noh, Jungsik
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1531-1541
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    • 2013
  • This paper proposes a new method of VaR forecasting using the conditional autoregressive VaR (CAViaR) models and information criteria. Instead of using a single CAViaR model, we propose to utilize several candidate CAViaR models during a forecasting period. By adopting the Akaike and Bayesian information criteria for quantile regression, we can update not only parameter estimates but also the CAViaR specifications. We also propose extended CAViaR models with a constant location parameter. An empirical study is provided to examine the performance of the proposed method. The results suggest that our method shows more stable performance than those using a single specification.

QUANTITATIVE ANALYSES USING 4D MODELS - AN EXPLORATIVE STUDY

  • Rogier Jongeling;Jonghoon Kim;Claudio Mourgues;Martin Fischer;Thomas Olofsson
    • International conference on construction engineering and project management
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    • 2005.10a
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    • pp.830-835
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    • 2005
  • 4D models help construction planners to develop and evaluate construction plans. However, current analyses using 4D models are mainly visual and limit the quantitative comparison of construction alternatives. This paper explores the usefulness of extracting quantitative information from 4D models to support time-space analyses. We use two 4D models of an industry test case to illustrate how to analyze 4D content quantitatively (i.e., work space areas and distances between concurrent activities). This paper shows how these two types of 4D content can be extracted from 4D models to support 4D-based-analysis and novel presentation of construction planning information. We suggest further research to formalize the content of 4D models to enable comparative quantitative analyses of construction planning alternatives. Formalized 4D content will enable the development of reasoning mechanisms that automate 4D-model-based analyses and provide the information content for informative presentations of construction planning information.

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Requirement Analysis on Lightweight CAD Models in Ship PLM Environment and Its Application Examples (조선 PLM 환경에서 경량 CAD 모델에 대한 요구사항 분석 및 적용 사례)

  • Cheon, Sanguk;Lee, Ji-Hoon;Park, Kwang-Phil;Suh, Heung-Won
    • Korean Journal of Computational Design and Engineering
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    • v.18 no.4
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    • pp.299-307
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    • 2013
  • Introduction of PLM in domestic shipyards is being retarded as ship PLM has yet to firm up return of investment and process integration. To implement a ship PLM system, it is required to share ship CAD model data in various design and manufacturing environments. Lightweight CAD models provide a promising solution for sharing CAD models in the product life cycle, which can expedite implementation of ship PLM in domestic shipyards in the near future. Compared to proprietary CAD models, it is easy for lightweight CAD models to be interfaced with various application systems and be connected to manufacturing information. In this paper, the reason why lightweight CAD models are necessary to implement a ship PLM system is addressed and current implementation results are introduced.

Concepts and Design Aspects of Granular Models of Type-1 and Type-2

  • Pedrycz, Witold
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.2
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    • pp.87-95
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    • 2015
  • In this study, we pursue a new direction for system modeling by introducing the concept of granular models, which produce results in the form of information granules (such as intervals, fuzzy sets, and rough sets). We present a rationale and several key motivating arguments behind the use of granular models and discuss their underlying design processes. The development of the granular model includes optimal allocation of information granularity through optimizing the criteria of coverage and specificity. The emergence and construction of granular models of type-2 and type-n (in general) is discussed. It is shown that achieving a suitable coverage-specificity tradeoff (compromise) is essential for developing granular models.

Utterance Verification Using Anti-models Based on Neighborhood Information (이웃 정보에 기초한 반모델을 이용한 발화 검증)

  • Yun, Young-Sun
    • MALSORI
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    • no.67
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    • pp.79-102
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    • 2008
  • In this paper, we investigate the relation between Bayes factor and likelihood ratio test (LRT) approaches and apply the neighborhood information of Bayes factor to building an alternate hypothesis model of the LRT system. To consider the neighborhood approaches, we contemplate a distance measure between models and algorithms to be applied. We also evaluate several methods to improve performance of utterance verification using neighborhood information. Among these methods, the system which adopts anti-models built by collecting mixtures of neighborhood models obtains maximum error rate reduction of 17% compared to the baseline, linear and weighted combination of neighborhood models.

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Development of BIM models and management of BIM data for waterworks maintenance (상수도시설물의 유지관리를 위한 BIM모델 개발 및 BIM 데이터 관리방안)

  • Park, Jaehyun;Lee, Hyundong;Kwak, Pilljae
    • Journal of Korean Society of Water and Wastewater
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    • v.28 no.6
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    • pp.669-679
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    • 2014
  • 3D-based BIM(Building Information Modeling) technologies can be utilized effectively as a means of systematic management of facility information for safety assurance and effective maintenance of waterworks facilities. In this study, BIM models of water treatment facilities that can be used as basic data for BIM-based maintenance of waterworks facilities were developed. Information exchange and generality of the developed BIM models were evaluated by conducting interoperability analysis of IFC(Industry Foundation Classes) conversion models. In addition, the application of COBie(Construction Operations Building information exchange) was recommended as an effective countermeasure to deal with technical limitation regarding exchange and utilization of facilities-related information through current IFC models. The results of this study can contribute to the development of BIM-based maintenance system for waterworks facilities.