• Title/Summary/Keyword: Customized Classification

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An Improvement study in Keyword-centralized academic information service - Based on Recommendation and Classification in NDSL - (키워드 중심 학술정보서비스 개선 연구 - NDSL 추천 및 분류를 중심으로 -)

  • Kim, Sun-Kyum;Kim, Wan-Jong;Lee, Tae-Seok;Bae, Su-Yeong
    • Journal of Korean Library and Information Science Society
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    • v.49 no.4
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    • pp.265-294
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    • 2018
  • Nowadays, due to an explosive increase in information, information filtering is very important to provide proper information for users. Users hardly obtain scholarly information from a huge amount of information in NDSL of KISTI, except for simple search. In this paper, we propose the service, PIN to solve this problem. Pin provides the word cloud including analyzed users' and others' interesting, co-occurence, and searched keywords, rather than the existing word cloud simply consisting of all keywords and so offers user-customized papers, reports, patents, and trends. In addition, PIN gives the paper classification in NDSL according to keyword matching based classification with the overlapping classification enabled-academic classification system for better search and access to solve this problem. In this paper, Keywords are extracted according to the classification from papers published in Korean journals in 2016 to design classification model and we verify this model.

Cluster-based Linear Projection and %ixture of Experts Model for ATR System (자동 목표물 인식 시스템을 위한 클러스터 기반 투영기법과 혼합 전문가 구조)

  • 신호철;최재철;이진성;조주현;김성대
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.3
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    • pp.203-216
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    • 2003
  • In this paper a new feature extraction and target classification method is proposed for the recognition part of FLIR(Forwar Looking Infrared)-image-based ATR system. Proposed feature extraction method is "cluster(=set of classes)-based"version of previous fisherfaces method that is known by its robustness to illumination changes in face recognition. Expecially introduced class clustering and cluster-based projection method maximizes the performance of fisherfaces method. Proposed target image classification method is based on the mixture of experts model which consists of RBF-type experts and MLP-type gating networks. Mixture of experts model is well-suited with ATR system because it should recognizee various targets in complexed feature space by variously mixed conditions. In proposed classification method, one expert takes charge of one cluster and the separated structure with experts reduces the complexity of feature space and achieves more accurate local discrimination between classes. Proposed feature extraction and classification method showed distinguished performances in recognition test with customized. FLIR-vehicle-image database. Expecially robustness to pixelwise sensor noise and un-wanted intensity variations was verified by simulation.

Discovering locally customized and future promising industries using patent analysis : Centered on the Case of Busan city (특허 분석을 통한 지역맞춤형 미래유망산업 발굴 및 도출에 관한 연구 : 부산 지역 사례를 중심으로)

  • Kim, Hyun-Woo;Shim, We;Kwon, Oh-Jin;Noh, Kyung-Ran
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.1
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    • pp.129-138
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    • 2017
  • The aim of this paper is to suggest methodology for local governments when discovering locally customized future promising industries with regard to policies of central government, regional competencies, and industrial promising. Firstly, key industries by region specified in '5-years regional industrial development master plan(2014)' were utilized. Secondly, science and technology competency by region was calculated with analyzing patent data in each key industries. Thirdly, industrial promising was verified by calculating Knowledge Stock and Activity Index based on measuring industry-IPC linkage. Based on the methodology proposed above, case study(case of Busan city) was done. Finally, 7 core industries and 94 candidates of future promising industries were extracted on the basis of 5 digit of KSIC subdivision. The methodology is expected to contribute local governments to establish evidence-based, efficient, and future-oriented local R&D roadmapping.

Study on Fatality Risk of Senior Driver with Aging Classification (초기·중기·후기 고령운전자의 사망자 발생위험도 분석과 시사점)

  • Choi, Jaesung
    • Journal of the Korean Society of Safety
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    • v.33 no.1
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    • pp.148-161
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    • 2018
  • A traffic fatality by young people marked average annual decrease of 4.5% since 2011. Meanwhile, a traffic fatality by senior over 65 years old marked average annual increase of 7.9% for the last five years which means that the annual increase of traffic fatality by senior will be a serious problem. This study started questioning that senior drivers over 65 years old did not retain the same causal factor of fatal traffic accidents and thus extensively analyzed a risk of it by age group quantitatively, dividing the senior driver group into the early, middle and latter stages. Depending on the aging level, the risk of traffic fatality showed a wide difference in seven different types of traffic accidents generally, and happened to increase with latter and middle parts of the senior driver more than the early part. Therefore, this study proposes four policy suggestions: 1) The senior driver need to be offered customized driving educations and the improvement of road environment is also recommended. 2) Political assistance is needed to support and guide a safety related technology installation for the new or existing car. 3) Renewal of driving license and an aptitude test(physical examination, cognitive test) for drivers over 75 years old should take in a less than 3 years and an additional road test is needed as occasion demands. 4) Like the United States and Europe, development and extension of customized treatment guidebook for medical teams who examine senior drivers is needed and establishment of education and administration system that a supervisor of driving license renewal can impose safety restriction and American anonymity reporting system is considered to institutionalize in the medium to longer term.

A Review of Recent Evidence on Trigeminal Neuralgia

  • Mee-Eun Kim;Hye-Kyoung Kim
    • Journal of Oral Medicine and Pain
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    • v.48 no.1
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    • pp.3-10
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    • 2023
  • This review aimed to update our knowledge of the classification, pathophysiology, prognosis, and treatment of trigeminal neuralgia (TN), with the intention of establishing better treatment protocols. The latest version of the International Classification of Headache Disorders uses an etiology-based approach to characterize TN patients, potentially contributing to the development of targeted treatment measures. Noticeable changes in the recent European Academy of Neurology guidelines for the management of TN include the use of magnetic resonance imaging for exclusion of secondary TN and differentiation of idiopathic and classical TN. Additionally, the use of botulinum toxin type A as an addon therapy for mid-term treatment of TN has also been included. Though there has been limited recent progress in the treatment of TN, previous studies emphasize the importance of customized, multidisciplinary management protocols that include drug therapy optimization; provision of continuous education and support; and timely referral of medically refractory patients for surgery in order to achieve favorable prognosis. Furthermore, slow but growing evidence on gene mutations will help elucidate the pathophysiology of TN and contribute to the development of targeted drugs that are effective and safe.

Core Keywords Extraction forEvaluating Online Consumer Reviews Using a Decision Tree: Focusing on Star Ratings and Helpfulness Votes (의사결정나무를 활용한 온라인 소비자 리뷰 평가에 영향을 주는 핵심 키워드 도출 연구: 별점과 좋아요를 중심으로)

  • Min, Kyeong Su;Yoo, Dong Hee
    • The Journal of Information Systems
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    • v.32 no.3
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    • pp.133-150
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    • 2023
  • Purpose This study aims to develop classification models using a decision tree algorithm to identify core keywords and rules influencing online consumer review evaluations for the robot vacuum cleaner on Amazon.com. The difference from previous studies is that we analyze core keywords that affect the evaluation results by dividing the subjects that evaluate online consumer reviews into self-evaluation (star ratings) and peer evaluation (helpfulness votes). We investigate whether the core keywords influencing star ratings and helpfulness votes vary across different products and whether there is a similarity in the core keywords related to star ratings or helpfulness votes across all products. Design/methodology/approach We used random under-sampling to balance the dataset. We progressively removed independent variables based on decreasing importance through backwards elimination to evaluate the classification model's performance. As a result, we identified classification models that best predict star ratings and helpfulness votes for each product's online consumer reviews. Findings We have identified that the core keywords influencing self-evaluation and peer evaluation vary across different products, and even for the same model or features, the core keywords are not consistent. Therefore, companies' producers and marketing managers need to analyze the core keywords of each product to highlight the advantages and prepare customized strategies that compensate for the shortcomings.

Surface-Engineered Graphene surface-enhanced Raman scattering Platform with Machine-learning Enabled Classification of Mixed Analytes

  • Jae Hee Cho;Garam Bae;Ki-Seok An
    • Journal of Sensor Science and Technology
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    • v.33 no.3
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    • pp.139-146
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    • 2024
  • Surface-enhanced Raman scattering (SERS) enables the detection of various types of π-conjugated biological and chemical molecules owing to its exceptional sensitivity in obtaining unique spectra, offering nondestructive classification capabilities for target analytes. Herein, we demonstrate an innovative strategy that provides significant machine learning (ML)-enabled predictive SERS platforms through surface-engineered graphene via complementary hybridization with Au nanoparticles (NPs). The hybridized Au NPs/graphene SERS platforms showed exceptional sensitivity (10-7 M) due to the collaborative strong correlation between the localized electromagnetic effect and the enhanced chemical bonding reactivity. The chemical and physical properties of the demonstrated SERS platform were systematically investigated using microscopy and spectroscopic analysis. Furthermore, an innovative strategy employing ML is proposed to predict various analytes based on a featured Raman spectral database. Using a customized data-preprocessing algorithm, the feature data for ML were extracted from the Raman peak characteristic information, such as intensity, position, and width, from the SERS spectrum data. Additionally, sophisticated evaluations of various types of ML classification models were conducted using k-fold cross-validation (k = 5), showing 99% prediction accuracy.

A Study on the Effect of Customized Education for Small and Medium-sized Businesses Handling Hazardous Chemicals (유해화학물질 취급 중소사업장을 대상으로 한 맞춤형 교육 효과에 관한 연구)

  • Lee, Hyo-Eun;Kim, Min-Gyu;Lee, Bong-Woo
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.6_2
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    • pp.979-986
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    • 2022
  • Chemical accidents are increasing day by day as the industry develops. To prevent such chemical accidents, Korea enacted the Chemicals Control Act. Through these laws, systematic management of chemical substances began. There are various positions in the companies. hazardous chemical supervisors, equipment and technical human, operators and employees. Chemicals-related education for each position should be provided. As a result of the survey, hazardous chemical supervisors and equipment and technical human liked the overall content of the Chemicals Control Act and the education subject on safety management standards for facilities. Conversely, the operators liked the course on how to wear personal protective equipment. The employees preferred subjects such as classification of chemical substances and prevention of chemical accidents. Currently, various modular textbooks are widely available. Rather than general education, it is necessary to select and provide customized subjects that are preferred and interested according to the position. Then it will be more effective in understanding harzardous chemical substances and in preventing chemical accidents.

Customized Coupon Recommendation Model based on Fuzzy AHP Reflecting User Preference (사용자 선호도를 반영한 FUZZY-AHP 기반 맞춤형 쿠폰 추천 모델)

  • Sim, Weon-Ik;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.395-401
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    • 2014
  • As social network service becomes common, the consumers use many discount coupons with which they can purchase goods via social commerce. Although, the quantities of coupons offered from social commerce are currently on the sharp increase, customized coupon service that reflects user preference is not offered. This paper proposes a coupon service method reflecting user's subjective inclination targeting food coupons to offer customized coupon service for social commerce. Towards this end, this paper conducts hierarchization of the factors that become standard in selecting coupons including food types, food prices, discount rates and the number of buyers. And then, this study classifies, extracts and offers the coupons using Fuzzy-AHP, a decision making support method that reflects subjective inclination. From the user satisfaction results on the extracted coupons, the users are generally satisfied: very satisfactory with 45%, satisfactory with 33% and fair with 22%, and there was no experiment participant, who was dissatisfied.

An Implementation of a Classification and Recommendation Method for a Music Player Using Customized Emotion (맞춤형 감성 뮤직 플레이어를 위한 음악 분류 및 추천 기법 구현)

  • Song, Yu-Jeong;Kang, Su-Yeon;Ihm, Sun-Young;Park, Young-Ho
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.4
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    • pp.195-200
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    • 2015
  • Recently, most people use android based smartphones and we can find music players in any smartphones. However, it's hard to find a personalized music player which applies user's preference. In this paper, we propose an emotion-based music player, which analyses and classifies the music with user's emotion, recommends the music, applies the user's preference, and visualizes the music by color. Through the proposed music player, user could be able to select musics easily and use an optimized application.