• Title/Summary/Keyword: decision hierarchy tree

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A Hybrid Index based on Aggregation R-tree for Spatio-Temporal Aggregation (시공간 집계정보를 위한 Aggregation R-tree 기반의 하이브리드 인덱스)

  • You, Byeong-Seob;Bae, Hae-Young
    • Journal of KIISE:Databases
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    • v.33 no.5
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    • pp.463-475
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    • 2006
  • In applications such as a traffic management system, analysis using a spatial hierarchy of a spatial data warehouse and a simple aggregation is required. Over the past few years, several studies have been made on solution using a spatial index. Many studies have focused on using extended R-tree. But, because it just provides either the current aggregation or the total aggregation, decision support of traffic policy required historical analysis can not be provided. This paper proposes hybrid index based on extended aR-tree for the spatio-temporal aggregation. The proposed method supports a spatial hierarchy and the current aggregation by the R-tree. The sorted hash table using the time structure of the extended aR-tree provides a temporal hierarchy and a historical aggregation. Therefore, the proposed method supports an efficient decision support with spatio-temporal analysis and is Possible currently traffic analysis and determination of a traffic policy with historical analysis.

Knowledge Extractions, Visualizations, and Inference from the big Data in Healthcare and Medical

  • Kim, Jin Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.5
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    • pp.400-405
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    • 2013
  • The purpose of this study is to develop a composite platform for knowledge extractions, visualizations, and inference. Generally, the big data sets were frequently used in the healthcare and medical area. To help the knowledge managers/users working in the field, this study is focused on knowledge management (KM) based on Data Mining (DM), Knowledge Distribution Map (KDM), Decision Tree (DT), RDBMS, and SQL-inference. The proposed mechanism is composed of five key processes. Firstly, in Knowledge Parsing, it extracts logical rules from a big data set by using DM technology. Then it transforms the rules into RDB tables. Secondly, through Knowledge Maintenance, it refines and manages the knowledge to be ready for the computing of knowledge distributions. Thirdly, in Knowledge Distribution process, we can see the knowledge distributions by using the DT mechanism.Fourthly, in Knowledge Hierarchy, the platform shows the hierarchy of the knowledge. Finally, in Inference, it deduce the conclusions by using the given facts and data.This approach presents the advantages of diversity in knowledge representations and inference to improve the quality of computer-based medical diagnosis.

Hierarchy analysis of computationally proposed 100 cases of new digital games based on the expected marketability (컴퓨테이셔널 방법론에 따라 제안된 100가지 미개발 게임 유형들에 대한 기대 시장성 기준의 위계 분석)

  • Kim, Ikhwan
    • Journal of Korea Game Society
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    • v.19 no.5
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    • pp.133-142
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    • 2019
  • In this study, 100 types of computationally proposed digital games were analyzed based on the expected marketability. The game classification methodology with five classification criteria proposed by Kim (2017) and the elimination method leveraged by the Decision Tree have been adopted as the methodology of the study. As a result, digital games could be classified into three groups. With the result, designers in the field will be able to leverage computational design methodology to develop a new type of digital game more efficiently by following the proposed hierarchy.

A Study on Evaluation of the Priority Order about Framework Data Building (기본지리정보 구축 우선순위 평가에 관한 연구)

  • 김건수;최윤수;조성길;이상미
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.11a
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    • pp.361-366
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    • 2004
  • Geographic Information has been used widely for landuse and management, city plan, and environment and disaster management, etc., But geographic information has been built for individual cases using various methods. Therefore, the discordancy in data, double investment, confusion of use and difficulty of decision supporting system have been occurred. In order to solve these problems, national government is need to framework database. This framework database was enacted for building and use of National Geographic Information System and focused on basic plan of the second national geographic information system. Also, the framework database was selected of eight fields by NGIS laws and 19 detailed items through meeting of framework committee since 2002. In this research, The 19 detailed items( road, railroad, coastline, surveying control point etc.,) of framework database consider a Priority order, In the result of this research, the framework database is obtain to a priority order for building and the national government will carry effectively out a budget for the framework database building. Each of 19 detailed items is grouping into using the priority order of the framework database by AHP analysis method and verified items by decision tree analysis method. The one of the highest priority order items is a road, which is important for building, continuous renovation, and maintain management for use.

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Predicting Discharge Rate of After-care patient using Hierarchy Analysis

  • Jung, Yong Gyu;Kim, Hee-Wan;Kang, Min Soo
    • International Journal of Advanced Culture Technology
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    • v.4 no.2
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    • pp.38-42
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    • 2016
  • In the growing data saturated world, the question of "whether data can be used" has shifted to "can it be utilized effectively?" More data is being generated and utilized than ever before. As the collection of data increases, data mining techniques also must become more and more accurate. Thus, to ensure this data is effectively utilized, the analysis of the data must be efficient. Interpretation of results from the analysis of the data set presented, have their own on the basis it is possible to obtain the desired data. In the data mining method a decision tree, clustering, there is such a relationship has not yet been fully developed algorithm actually still impact of various factors. In this experiment, the classification method of data mining techniques is used with easy decision tree. Also, it is used special technology of one R and J48 classification technique in the decision tree. After selecting a rule that a small error in the "one rule" in one R classification, to create one of the rules of the prediction data, it is simple and accurate classification algorithm. To create a rule for the prediction, we make up a frequency table of each prediction of the goal. This is then displayed by creating rules with one R, state-of-the-art, classification algorithm while creating a simple rule to be interpreted by the researcher. While the following can be correctly classified the pattern specified in the classification J48, using the concept of a simple decision tree information theory for configuring information theory. To compare the one R algorithm, it can be analyzed error rate and accuracy. One R and J48 are generally frequently used two classifications${\ldots}$

Prioritizing the Building Order of the Geographic Framework Data (기본지리정보 항목별 구출 우선순위 평가에 관한 연구)

  • Choi Yun-Soo;Jun Chul-Min;Kim Gun-Soo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.3
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    • pp.269-275
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    • 2004
  • Geographic data have widely been applied in different areas including landuse, city planning and management, environment, disaster management and even daily use of citizens. Since geographic data have been built individually using different methods, many problems such as data inconsistency, duplicated investment, and confusion in decision making have arisen. Thus, the necessity of national framework database that can be shared by different areas has increased. As a result, eight fields of the framework database were defined by NGIS Law and 19 detailed items were selected. This study used the AHP (Analytical Hierarchy Process) and the decision tree to evaluate the relative importance of the items (eg. roads, railroads, coastline, surveying control points, and etc.) and presented the groups classified according to the priorities of the items. The result of this study is believed to contribute to effective budget planning for building national framework database.

Data Cude Index to Support Integrated Multi-dimensional Concept Hierarchies in Spatial Data Warehouse (공간 데이터웨어하우스에서 통합된 다차원 개념 계층 지원을 위한 데이터 큐브 색인)

  • Lee, Dong-Wook;Baek, Sung-Ha;Kim, Gyoung-Bae;Bae, Hae-Young
    • Journal of Korea Multimedia Society
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    • v.12 no.10
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    • pp.1386-1396
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    • 2009
  • Most decision support functions of spatial data warehouse rely on the OLAP operations upon a spatial cube. Meanwhile, higher performance is always guaranteed by indexing the cube, which stores huge amount of pre-aggregated information. Hierarchical Dwarf was proposed as a solution, which can be taken as an extension of the Dwarf, a compressed index for cube structures. However, it does not consider the spatial dimension and even aggregates incorrectly if there are redundant values at the lower levels. OLAP-favored Searching was proposed as a spatial hierarchy based OLAP operation, which employs the advantages of R-tree. Although it supports aggregating functions well against specified areas, it ignores the operations on the spatial dimensions. In this paper, an indexing approach, which aims at utilizing the concept hierarchy of the spatial cube for decision support, is proposed. The index consists of concept hierarchy trees of all dimensions, which are linked according to the tuples stored in the fact table. It saves storage cost by preventing identical trees from being created redundantly. Also, it reduces the OLAP operation cost by integrating the spatial and aspatial dimensions in the virtual concept hierarchy.

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Video Ranking Model: a Data-Mining Solution with the Understood User Engagement

  • Chen, Yongyu;Chen, Jianxin;Zhou, Liang;Yan, Ying;Huang, Ruochen;Zhang, Wei
    • Journal of Multimedia Information System
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    • v.1 no.1
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    • pp.67-75
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    • 2014
  • Nowadays as video services grow rapidly, it is important for the service providers to provide customized services. Video ranking plays a key role for the service providers to attract the subscribers. In this paper we propose a weekly video ranking mechanism based on the quantified user engagement. The traditional QoE ranking mechanism is relatively subjective and usually is accomplished by grading, while QoS is relatively objective and is accomplished by analyzing the quality metrics. The goal of this paper is to establish a ranking mechanism which combines the both advantages of QoS and QoE according to the third-party data collection platform. We use data mining method to classify and analyze the collected data. In order to apply into the actual situation, we first group the videos and then use the regression tree and the decision tree (CART) to narrow down the number of them to a reasonable scale. After that we introduce the analytic hierarchy process (AHP) model and use Elo rating system to improve the fairness of our system. Questionnaire results verify that the proposed solution not only simplifies the computation but also increases the credibility of the system.

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The State Attribute and Grade Influence Structure for the RC Bridge Deck Slabs by Information Entropy (정보 엔트로피에 의한 RC 교량 상판의 상태속성 및 등급 영향 구조 분석)

  • Hwang, Jin-Ha;Park, Jong-Hoi;An, Seoung-Su
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.1
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    • pp.61-71
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    • 2010
  • The attributes related to the health condition of RC deck slabs are analyzed to help us identify and rate the safety level of the bridges in this study. According to the related reports the state assessment for the outward aspects of bridges is the important and critical part for rating the overall structural safety. In this respect, the careful identification for the various state attributes make the field inspection and structural diagnosis very effective. This study analyzes the influence of the state attributes on evaluation classes and the relationship of them by the inductive reasoning, which raise the understanding and performance for evaluation work, and support the logical approach for the state assessment. ID3 algorithm applied to the case set which is constructed from the field reports indicates the main attributes and the precedence governing the assessment, and derives the decision hierarchy for the state assessment.

Classification and Analysis of Data Mining Algorithms (데이터마이닝 알고리즘의 분류 및 분석)

  • Lee, Jung-Won;Kim, Ho-Sook;Choi, Ji-Young;Kim, Hyon-Hee;Yong, Hwan-Seung;Lee, Sang-Ho;Park, Seung-Soo
    • Journal of KIISE:Databases
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    • v.28 no.3
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    • pp.279-300
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    • 2001
  • Data mining plays an important role in knowledge discovery process and usually various existing algorithms are selected for the specific purpose of the mining. Currently, data mining techniques are actively to the statistics, business, electronic commerce, biology, and medical area and currently numerous algorithms are being researched and developed for these applications. However, in a long run, only a few algorithms, which are well-suited to specific applications with excellent performance in large database, will survive. So it is reasonable to focus our effort on those selected algorithms in the future. This paper classifies about 30 existing algorithms into 7 categories - association rule, clustering, neural network, decision tree, genetic algorithm, memory-based reasoning, and bayesian network. First of all, this work analyzes systematic hierarchy and characteristics of algorithms and we present 14 criteria for classifying the algorithms and the results based on this criteria. Finally, we propose the best algorithms among some comparable algorithms with different features and performances. The result of this paper can be used as a guideline for data mining researches as well as field applications of data mining.

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