• Title/Summary/Keyword: Multinomial model

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Assortment Optimization under Consumer Choice Behavior in Online Retailing

  • Lee, Joonkyum;Kim, Bumsoo
    • Management Science and Financial Engineering
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    • v.20 no.2
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    • pp.27-31
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    • 2014
  • This paper studies the assortment optimization problem in online retailing by using a multinomial logit model in order to take consumer choice behavior into account. We focus on two unique features of online purchase behavior: first, there exists increased amount of uncertainty (e.g., size and color of merchandize) in online shopping as customers cannot experience merchandize directly. This uncertainty is captured by the scale parameter of a Gumbel distribution; second, online shopping entails unique shopping-related disutility (e.g., waiting time for delivery and security concerns) compared to offline shopping. This disutility is controlled by the changes in the observed part of utility function in our model. The impact of changes in uncertainty and disutility on the expected profit does not exhibit obvious structure: the expected profit may increase or decrease depending on the assortment. However, by analyzing the structure of the optimal assortment based on convexity property of the profit function, we show that the cardinality of the optimal assortment decreases and the maximum expected profit increases as uncertainty or disutility decreases. Therefore, our study suggests that it is important for managers of online retailing to reduce uncertainty and disutility involved in online purchase process.

Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety

  • Yeom, Ha-Neul;Hwang, Myunggwon;Hwang, Mi-Nyeong;Jung, Hanmin
    • Journal of Information Science Theory and Practice
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    • v.2 no.3
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    • pp.29-39
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    • 2014
  • In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

The Effects of The Minimum Wage On Working Poor's Poverty-Exit Possibility (최저임금이 근로빈곤 탈출에 미치는 효과)

  • Lee, Sikyoon
    • Korean Journal of Labor Studies
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    • v.19 no.1
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    • pp.35-64
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    • 2013
  • This paper explores whether or not a minimum wage increase can do much to alleviate working poor. For this purpose, I analyze transitions from working poor to working non-poor and to unemployment or non-economically active states, using KLIPS (Korea Labor and Income Panel Study). This study uses the multilevel multinomial logit model to control unobserved individual heterogenous characteristics. It finds that a minimum wage increase tends to cause a higher probability of transitions from working poor to working non-poor. It is also discovered that a minimum wage increase is not negatively related with the persistence of the working state. It is concluded that minimum wage increases are likely to be effective in improving the living standards of the 'working poor'.

An Empirical Analysis of the Factors Affecting the Types of 6th Industrialization Business of Fishery Households (어가의 어촌 6차산업화 사업유형 결정요인 분석)

  • Lee, Sejin;An, Donghwan
    • Journal of Korean Society of Rural Planning
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    • v.27 no.1
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    • pp.85-94
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    • 2021
  • The purpose of this study is to investigate the factors affecting the types of the 6th industrialization of fishery households. In this study we tried to explain the significance of the demographic and managerial characteristics of fishery households when they choose the types of the 6th industrialization business. Multinomial logistic model was used for this analysis. This study shows that the household and fishery management characteristics, main method of fishing, and regional factors matters for fishery households to choose their business types. Our results implies that it is necessary to reflect the detailed support measures differentiated by business types when implementing the 6th industrialization policy for fishery sector. In addition, the sixth industrialization of fishery should not be limited to marine products, but agricultural products produced in fishing villages should be included.

Classifications of Hadiths based on Supervised Learning Techniques

  • AbdElaal, Hammam M.;Bouallegue, Belgacem;Elshourbagy, Motasem;Matter, Safaa S.;AbdElghfar, Hany A.;Khattab, Mahmoud M.;Ahmed, Abdelmoty M.
    • International Journal of Computer Science & Network Security
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    • v.22 no.11
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    • pp.1-10
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    • 2022
  • This study aims to build a model is capable of classifying the categories of hadith, according to the reliability of hadith' narrators (sahih, hassan, da'if, maudu) and according to what was attributed to the Prophet Muhammad (saying, doing, describing, reporting ) using the supervised learning algorithms, with a view to discover a relationship between these classifications, based on the outputs of this model, which might be useful to avoid the controversy and useless debate on automatic classifications of hadith, using some of the statistical methods such as chi-square, information gain and association rules. The experimental results showed that there is a relation between these classifications, most of Sahih hadiths are belong to saying class, and most of maudu hadiths are belong to reporting class. Also the best classifier had given high accuracy was MultinomialNB, it achieved higher accuracy reached up to 0.9708 %, for his ability to process high dimensional problems and identifying the most important features that are relevant to target data in training stage. Followed by LinearSVC classifier, reached up to 0.9655, and finally, KNeighborsClassifier reached up to 0.9644.

Exploring Spatio-temporal Patterns of Population and its Influential Factors in Jeonju (거주인구의 시공간 변화 및 영향요인 분석: 전라북도 전주시 사례를 중심으로)

  • Jicheol Yang;Jooae Kim;Kuk Cho;Sangwan Lee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.3
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    • pp.251-258
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    • 2023
  • This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

An Empirical Analysis on the Determinants of Residential Mobility and Reclassifying Urban and Rural Areas (도시와 농촌의 재유형화와 주거이동 결정요인 분석)

  • Heewon Chang;Donghwan An
    • Journal of Korean Society of Rural Planning
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    • v.30 no.2
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    • pp.79-96
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    • 2024
  • The purpose of this study is to analyze the factors affecting residential mobility between urban and rural. After classifying urban and rural region based on discriminatory attributes of the regions, we applied a multinomial logistic model, using the sample data of 2020 Korea Population and Housing Census. The major findings are as follows. The young highly educated in cities avoided rural. The young less educated in rural engaged in 2, 3th industries as well as agricultural industry, but remained in low-paying and unstable jobs. In addition, various classes moved to rural and rising house prices in cities pushed people to rural. Therefore, it is necessary to develop diversified regional industry models and provide opportunities for high quality and stable jobs in rural by linking industrial demand, education and jobs. Also, preserving the rural environment, settlement conditions and residential environment are needed for satisfying various needs of urban residents who migrate to rural areas. While regional policies so far have focused on maintaining the population size and promoting a population influx, rural development and population policies should be established in a way that responds to diverse population classes in an era of population decline.

A probabilistic information retrieval model by document ranking using term dependencies (용어간 종속성을 이용한 문서 순위 매기기에 의한 확률적 정보 검색)

  • You, Hyun-Jo;Lee, Jung-Jin
    • The Korean Journal of Applied Statistics
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    • v.32 no.5
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    • pp.763-782
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    • 2019
  • This paper proposes a probabilistic document ranking model incorporating term dependencies. Document ranking is a fundamental information retrieval task. The task is to sort documents in a collection according to the relevance to the user query (Qin et al., Information Retrieval Journal, 13, 346-374, 2010). A probabilistic model is a model for computing the conditional probability of the relevance of each document given query. Most of the widely used models assume the term independence because it is challenging to compute the joint probabilities of multiple terms. Words in natural language texts are obviously highly correlated. In this paper, we assume a multinomial distribution model to calculate the relevance probability of a document by considering the dependency structure of words, and propose an information retrieval model to rank a document by estimating the probability with the maximum entropy method. The results of the ranking simulation experiment in various multinomial situations show better retrieval results than a model that assumes the independence of words. The results of document ranking experiments using real-world datasets LETOR OHSUMED also show better retrieval results.

Development of Mode Choice Model and Applications Considering Connectivity of Express Way (고속도로 연계성을 반영한 고속철도 수단선택모형 개발 및 적용)

  • Cho, Hang-Ung;Chung, Sung-Bong;Kim, Si-Gon;Oh, Jae-Hak
    • Journal of the Korean Society for Railway
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    • v.14 no.4
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    • pp.383-389
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    • 2011
  • Until now, in planning and constructing KTX and the Express Way, the connectivity and transfer between these facilities have not been considered. In this study the effect of mode choice behavior by connecting KTX and the Express Way is analyzed through estimating Multinomial Logit Model and Binary Logit Model. The SP and RP surveys to develop these models were carried out and the data were selected from the passengers using the KTX station, Express Bus Terminals and Rest Areas in the Express Way. To test the effect of connectivity and transfer in the field, the case study for Dongtan KTX station was carried out. According to the results, connecting the KTX station and the Express Way has the effect of increasing the demand by 30%. And this is caused by saving about 120 minutes of traveling time from Seoul to Pusan. This study shows that the connectivity and transfer can increase the efficiency of transportation system and the improvement in the mobility and accessibility will maximize the usages of these two facilities.

Wife-older Marriage and Economic Factors : Empirical Analysis (우리나라 여성연상 결혼의 경제적 요인 : 실증분석)

  • Sung, Nak-Il;Jo, Dong-Hyuk
    • Korea journal of population studies
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    • v.33 no.3
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    • pp.1-30
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    • 2010
  • This study examines difference in age at marriage between spouses and more importantly, investigates into the economic and social factors affecting the ratio or probability of wife-older marriages. Empirical analysis is carried out by applying both logit model and multinomial logit model to an independently pooled cross-section over 2004-2007. The data was collected mainly from the micro data service system of the Statistics Korea. Empirical results indicate that a wife-older marriage was more likely as a wife was more educated and was a larger income earner than a husband. On the other hand, a wife's educational and income level themselves had few systematic relationships with the probability of a wife-older marriage. The probability of a wife-older marriage tended to decrease(increase) when a husband's(a wife's) marriage was the second' The study calculates the average marginal effect of difference in the income level between spouses on the probability of a wife-older marriage, which is -0.007. That is, the probability of a wife-older marriage increases by 0.7% as a husband's income level is 1 million Korean Won less than a wife's. This results presents empirical evidence against widely distributed misconception on wife-older marriage in the mass media.