• Title, Summary, Keyword: scoring model

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Design and Implementation of an Automatic Scoring Model Using a Voting Method for Descriptive Answers (투표 기반 서술형 주관식 답안 자동 채점 모델의 설계 및 구현)

  • Heo, Jeongman;Park, So-Young
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.8
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    • pp.17-25
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    • 2013
  • TIn this paper, we propose a model automatically scoring a student's answer for a descriptive problem by using a voting method. Considering the model construction cost, the proposed model does not separately construct the automatic scoring model per problem type. In order to utilize features useful for automatically scoring the descriptive answers, the proposed model extracts feature values from the results, generated by comparing the student's answer with the answer sheet. For the purpose of improving the precision of the scoring result, the proposed model collects the scoring results classified by a few machine learning based classifiers, and unanimously selects the scoring result as the final result. Experimental results show that the single machine learning based classifier C4.5 takes 83.00% on precision while the proposed model improve the precision up to 90.57% by using three machine learning based classifiers C4.5, ME, and SVM.

Research on the E-Commerce Credit Scoring Model Using the Gaussian Density Function

  • Xiao, Qiang;He, Rui-chun;Zhang, Wei
    • Journal of Information Processing Systems
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    • v.11 no.2
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    • pp.173-183
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    • 2015
  • At present, it is simple to the electronic commerce credit scoring model, as a brush credit phenomenon in E-commerce has emerged. This phenomenon affects the judgment of consumers and hinders the rapid development of E-commerce. In this paper, that E-commerce credit evaluation model that uses a Gaussian density function is put forward by density test and the analysis for the anomalies of E-commerce credit rating, it can be fond out the abnormal point in credit scoring, these points were calculated by nonlinear credit scoring algorithm, thus it can effectively improve the current E-commerce credit score, and enhance the accuracy of E-commerce credit score.

Development of Scoring Model on Customer Attrition Probability by Using Data Mining Techniques

  • Han, Sang-Tae;Lee, Seong-Keon;Kang, Hyun-Cheol;Ryu, Dong-Kyun
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.271-280
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    • 2002
  • Recently, many companies have applied data mining techniques to promote competitive power in the field of their business market. In this study, we address how data mining, that is a technique to enable to discover knowledge from a deluge of data, Is used in an executed project in order to support decision making of an enterprise. Also, we develope scoring model on customer attrition probability for automobile-insurance company using data mining techniques. The development of scoring model in domestic insurance is given as an example concretely.

Scoring models to detect foreign exchange money laundering (외국환 거래의 자금세탁 혐의도 점수모형 개발에 관한 연구)

  • Hong, Seong-Ik;Moon, Tae-Hee;Sohn, So-Young
    • IE interfaces
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    • v.18 no.3
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    • pp.268-276
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    • 2005
  • In recent years, the money Laundering crimes are increasing by means of foreign exchange transactions. Our study proposes four scoring models to provide early warning of the laundering in foreign exchange transactions for both inward and outward remittances: logistic regression model, decision tree, neural network, and ensemble model which combines the three models. In terms of accuracy of test data, decision tree model is selected for the inward remittance and an ensemble model for the outward remittance. From our study results, the accumulated number of transaction turns out to be the most important predictor variable. The proposed scoring models deal with the transaction level and is expected to help the bank teller to detect the laundering related transactions in the early stage.

Polyclass in Data Mining (데이터 마이닝에서의 폴리클라스)

  • 구자용;박헌진;최대우
    • The Korean Journal of Applied Statistics
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    • v.13 no.2
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    • pp.489-503
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    • 2000
  • Data mining means data analysis and model selection using various types of data in order to explore useful information and knowledge for making decisions. Examples of data mining include scoring for credit analysis of a new customer and scoring for churn management, where the customers with high scores are given special attention. In this paper, scoring is interpreted as a modeling process of the conditional probability and polyclass scoring method is described. German credit data, a PC communication company data and a mobile communication company data are used to compare the performance of polyclass scoring method with that of the scoring method based on a tree model.

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External Validation of a Clinical Scoring System for Hematuria

  • Lee, Seung Bae;Kim, Hyung Suk;Kim, Myong;Ku, Ja Hyeon
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.16
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    • pp.6819-6822
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    • 2014
  • Background: The aim of this study was to evaluate the accuracy of a new scoring system in Korean patients with hematuria at high risk of bladder cancer. Materials and Methods: A total of 319 consecutive patients presenting with painless hematuria without a history of bladder cancer were analyzed, from the period of August 2012 to February 2014. All patients underwent clinical examination, and 22 patients with incomplete data were excluded from the final validation data set. The scoring system included four clinical parameters: age (${\geq}50$ = 2 vs. <50 =1), gender (male = 2 vs. female = 1), history of smoking (smoker/ex-smoker = 4 vs. non-smoker = 2) and nature of the hematuria (gross = 6 vs. microscopic = 2). Results: The area under the receiver-operating characteristic curve (95% confidence interval) of the scoring system was 0.718 (0.655-0.777). The calibration plot demonstrated a slight underestimation of bladder cancer probability, but the model had reasonable calibration. Decision curve analysis revealed that the use of model was associated with net benefit gains over the treat-all strategy. The scoring system performed well across a wide range of threshold probabilities (15%-45%). Conclusions: The scoring system developed is a highly accurate predictive tool for patients with hematuria. Although further improvements are needed, utilization of this system may assist primary care physicians and other healthcare practitioners in determining a patient's risk of bladder cancer.

Measurement of Public Research Outcomes: A Technology Valuation Method

  • Park, Jung-Min;Lim, Seong-Il;Seol, Sung-Soo
    • Asian Journal of Innovation and Policy
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    • v.6 no.2
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    • pp.206-224
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    • 2017
  • This article proposes a logic model for assessing the performance of the outcome of public research as a technology valuation method. It consists of two parts and eight steps. The first part is a scoring system and the second part is a validation process of the performance index derived from scoring by valuation method. The scoring in the first part generally requires a focus group method to find out the value drivers and make an evaluation table. The reason why we call it the technology valuation method is that the first part is derived from the simple evaluation of technology value using checklists for value drive. The second part is the regular technology valuation process. The model is designed for the measurement of unquantifiable outcome. Is knowledge or scientific outcome comparable to the measured outcome? If possible, how big is the unquantifiable outcome? This model is based on financial valuation techniques with clear or acceptable market data. Therefore, it cannot work solely for unquantifiable outcomes without comparable measurable outcomes, unlike economic valuation.

Development of a Scoring Model for Evaluating the Rural Healthy and Longevity Village Project using DEA and AHP (DEA와 AHP기법을 이용한 농촌건강장수마을사업 평가모형 개발)

  • Suh, Kyo;Han, Yi-Cheol;Lee, Ji-Min;Lee, Jeong-Jae
    • Journal of Korean Society of Rural Planning
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    • v.12 no.4
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    • pp.1-11
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    • 2006
  • Recently many administrative institutes try to improve the viability of rural villages. For increasing the viability, not only infrastructures but internal vitality is necessary in rural villages. Nonetheless, most of governmental projects have been focused on infrastructures. For this reason, RDA(Rural Development Administration) designed and performed the RHL(Rural Healthy and Longevity village) project. This RHL project is not easy to evaluate the outcome because it consists of very intangible project items. In this paper, we developed a scoring model to evaluate the result of the RHL project. The scoring model based on DEA(Data Envelopment Analysis) was suggested to evaluate the quantity of personal activities in each village. Personal activities are classified into five categories: regional life, social life, productive life, outdoor life and indoor life. Evaluating indices of each category are developed and weighting values are evaluated by AHP(Analytic Hierarchy Process). The developed model was applied to Kumsan village and examined its applicability.

A Novel Molecular Grading Model: Combination of Ki67 and VEGF in Predicting Tumor Recurrence and Progression in Non-invasive Urothelial Bladder Cancer

  • Chen, Jun-Xing;Deng, Nan;Chen, Xu;Chen, Ling-Wu;Qiu, Shao-Peng;Li, Xiao-Fei;Li, Jia-Ping
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.5
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    • pp.2229-2234
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    • 2012
  • Purpose: To assess efficacy of Ki67 combined with VEGF as a molecular grading model to predict outcomes with non-muscle invasive bladder cancer (NMIBC). Materials: 72 NMIBC patients who underwent transurethral resection (TUR) followed by routine intravesical instillations were retrospectively analyzed in this study. Univariate and multivariate analyses were performed to confirm the prognostic values of the Ki67 labeling index (LI) and VEGF scoring for tumor recurrence and progression. Results: The novel molecular grading model for NMIBC contained three molecular grades including mG1 (Ki67 $LI{\leq}25%$, VEGF $scoring{\leq}8$), mG2 (Ki67 LI>25%, VEGF $scoring{\leq}8$; or Ki67 $LI{\leq}25%$, VEGF scoring > 8), and mG3 (Ki67 LI > 25%, VEGF scoring > 8), which can indicate favorable, intermediate and poor prognosis, respectively. Conclusions: The described novel molecular grading model utilizing Ki67 LI and VEGF scoring is helpful to effectively and accurately predict outcomes and optimize personal therapy.

Comparative Study of Exposure Potential and Toxicity Factors used in Chemical Ranking and Scoring System (화학물질 우선순위선정 시스템에서 고려되는 노출.독성인자 비교연구)

  • An, Youn-Joo;Jeong, Seung-Woo;Kim, Min-Jin;Yang, Chang-Yong
    • Environmental health and toxicology
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    • v.24 no.2
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    • pp.95-105
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    • 2009
  • Chemical Ranking and Scoring (CRS) system is a useful tool to screen priority chemicals of large body of substances. The relative ranking of chemicals based on CRS system has served as a decision-making support tools. Exposure potential and toxicity are significant parameters in CRS system, and there are differences in evaluating those parameters in each CRS system. In this study, the parameters of exposure potential, human toxicity, and ecotoxicity were extensively compared. In addition the scoring methods in each parameter were analyzed. The CRS systems considered in this study include the CHEMS-1 (Chemical Hazard Evaluation for Management Strategies), SCRAM (Scoring and Ranking Assessment Model), EURAM (European Union Risk Ranking Method), ARET (Accelerated Reduction/Elimination of Toxics), and CRS-Korea. An comparative analysis of the several CRS systems is presented based on their assessment parameters and scoring methods.