• Title/Summary/Keyword: Mining design

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Critical Assessment on Performance Management Systems for Health and Fitness Club using Balanced Score Card

  • Samina Saleem;Hussain Saleem;Abida Siddiqui;Umer Sheikh;Muhammad Asim;Jamshed Butt;Ali Muhammad Aslam
    • International Journal of Computer Science & Network Security
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    • v.24 no.7
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    • pp.177-185
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    • 2024
  • Web science, a general discipline of learning is presently at high demand of expertise with ideas to develop software-based WebApps and MobileApps to facilitate user or customer demand e.g. shopping etc. electronically with the access at their smartphones benefitting the business enterprise as well. A worldwide-computerized reservation network is used as a single point of access for reserving airline seats, hotel rooms, rental cars, and other travel related items directly or via web-based travel agents or via online reservation sites with the advent of social-web, e-commerce, e-business, from anywhere-on-earth (AoE). This results in the accumulation of large and diverse distributed databases known as big data. This paper describes a novel intelligent web-based electronic booking framework for e-business with distributed computing and data mining support with the detail of e-business system flow for e-Booking application architecture design using the approaches for distributed computing and data mining tools support. Further, the importance of business intelligence and data analytics with issues and challenges are also discussed.

Review on Quantitative Measures of Robustness for Building Structures Against Disproportionate Collapse

  • Jiang, Jian;Zhang, Qijie;Li, Liulian;Chen, Wei;Ye, Jihong;Li, Guo-Qiang
    • International Journal of High-Rise Buildings
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    • v.9 no.2
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    • pp.127-154
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    • 2020
  • Disproportionate collapse triggered by local structural failure may cause huge casualties and economic losses, being one of the most critical civil engineering incidents. It is generally recognized that ensuring robustness of a structure, defined as its insensitivity to local failure, is the most acceptable and effective method to arrest disproportionate collapse. To date, the concept of robustness in its definition and quantification is still an issue of controversy. This paper presents a detailed review on about 50 quantitative measures of robustness for building structures, being classified into structural attribute-based and structural performance-based measures (deterministic and probabilistic). The definition of robustness is first described and distinguished from that of collapse resistance, vulnerability and redundancy. The review shows that deterministic measures predominate in quantifying structural robustness by comparing the structural responses of an intact and damaged structure. The attribute-based measures based on structural topology and stiffness are only applicable to elastic state of simple structural forms while the probabilistic measures receive growing interest by accounting for uncertainties in abnormal events, local failure, structural system and failure-induced consequences, which can be used for decision-making tools. There is still a lack of generalized quantifications of robustness, which should be derived based on the definition and design objectives and on the response of a structure to local damage as well as the associated consequences of collapse. Critical issues and recommendations for future design and research on quantification of robustness are provided from the views of column removal scenarios, types of structures, regularity of structural layouts, collapse modes, numerical methods, multiple hazards, degrees of robustness, partial damage of components, acceptable design criteria.

Analyzing the weblog data of a shopping mall using process mining (프로세스 마이닝을 이용한 쇼핑몰 웹로그 데이터 분석)

  • Kim, Chae-Young;Yong, Hye-Ryeon;Hwang, Hyun-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.11
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    • pp.777-787
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    • 2020
  • With the development of the Internet and the spread of mobile devices, the online market is growing rapidly. As the number of customers using online shopping malls explodes, research is being conducted on the analysis of usage behavior from customer data, personalized product recommendations, and service development. Thus, this paper seeks to analyze the overall process of online shopping malls through process mining, and to identify the factors that influence users' purchases. The data used are from a large online shopping mall, and R was the analysis tool. The results show that customer activity was most prominent in categories with event elements, such as unconventional discounts and monthly giveaway events. On the other hand, searches, logins, and campaign activity were found to be less relevant than their importance. Those are very important, because they can provide clues to a customer's information and needs. Therefore, it is necessary to refine the recommendations from related search words, and to manage activity, such as coupons provided when customers log in. In addition to the previous discussion, this paper proposes various business strategies to enhance the competitiveness of online shopping malls and to increase profits.

Page Logging System for Web Mining Systems (웹마이닝 시스템을 위한 페이지 로깅 시스템)

  • Yun, Seon-Hui;O, Hae-Seok
    • The KIPS Transactions:PartC
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    • v.8C no.6
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    • pp.847-854
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    • 2001
  • The Web continues to grow fast rate in both a large aclae volume of traffic and the size and complexity of Web sites. Along with growth, the complexity of tasks such as Web site design Web server design and of navigating simply through a Web site have increased. An important input to these design tasks is the analysis of how a web site is being used. The is paper proposes a Page logging System(PLS) identifying reliably user sessions required in Web mining system PLS consists of Page Logger acquiring all the page accesses of the user Log processor producing user session from these data, and statements to incorporate a call to page logger applet. Proposed PLS abbreviates several preprocessing tasks which spends a log of time and efforts that must be performed in Web mining systems. In particular, it simplifies the complexity of transaction identification phase through acquiring directly the amount of time a user stays on a page. Also PLS solves local cache hits and proxy IPs that create problems with identifying user sessions from Web sever log.

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Data-mining modeling for the prediction of wear on forming-taps in the threading of steel components

  • Bustillo, Andres;Lopez de Lacalle, Luis N.;Fernandez-Valdivielso, Asier;Santos, Pedro
    • Journal of Computational Design and Engineering
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    • v.3 no.4
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    • pp.337-348
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    • 2016
  • An experimental approach is presented for the measurement of wear that is common in the threading of cold-forged steel. In this work, the first objective is to measure wear on various types of roll taps manufactured to tapping holes in microalloyed HR45 steel. Different geometries and levels of wear are tested and measured. Taking their geometry as the critical factor, the types of forming tap with the least wear and the best performance are identified. Abrasive wear was observed on the forming lobes. A higher number of lobes in the chamber zone and around the nominal diameter meant a more uniform load distribution and a more gradual forming process. A second objective is to identify the most accurate data-mining technique for the prediction of form-tap wear. Different data-mining techniques are tested to select the most accurate one: from standard versions such as Multilayer Perceptrons, Support Vector Machines and Regression Trees to the most recent ones such as Rotation Forest ensembles and Iterated Bagging ensembles. The best results were obtained with ensembles of Rotation Forest with unpruned Regression Trees as base regressors that reduced the RMS error of the best-tested baseline technique for the lower length output by 33%, and Additive Regression with unpruned M5P as base regressors that reduced the RMS errors of the linear fit for the upper and total lengths by 25% and 39%, respectively. However, the lower length was statistically more difficult to model in Additive Regression than in Rotation Forest. Rotation Forest with unpruned Regression Trees as base regressors therefore appeared to be the most suitable regressor for the modeling of this industrial problem.

A Basic Study on the Application of Text-Maining Method for Qualitative Evaluation through Barrier Free Certification in School Facilities (학교시설의 장애물 없는 생활환경(Barrier Free) 인증 사례를 통한 정성평가 텍스트마이닝 기법 적용에 관한 기초연구)

  • Yun, Pyeong-Se;Lee, Jong-Kuk
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.19 no.1
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    • pp.25-35
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    • 2020
  • Since the introduction and operation of BF certification, a total of 6,432 certificates has been issued until February 2020, of which educational research facilities make 1,091 cases (754 preliminary certification, 337 main certification) out of 6,237 buildings, acquiring BF certification of about 20%. Qualitative evaluation is conducted with focus on the three items of BF-certified building evaluation index, which are medium facilities, internal facilities, and sanitary facilities, and major keywords are the deducted through the Text Mining analysis of the derived results. As a result, problems with access paths occurred in the case of the facilities, and assessment indicators for users were found to be necessary among the assessment of the steps of the internal facilities. Finally, we could see that sanitation facilities needed to improve toilets installed in residential development facilities. Based on the results obtained, the study seeks to suggest directions for improving the evaluation index required for BF-certified school facilities.

Estimation of spatial autocorrelation variations of uncertain geotechnical properties for the frozen ground

  • Wang, Di;Wang, Tao;Xu, Daqing;Zhou, Guoqing
    • Geomechanics and Engineering
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    • v.22 no.4
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    • pp.339-348
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    • 2020
  • The uncertain geotechnical properties of frozen soil are important evidence for the design, operation and maintenance of the frozen ground. The complex geological, environmental and physical effects can lead to the spatial variations of the frozen soil, and the uncertain mechanical properties are the key factors for the uncertain analysis of frozen soil engineering. In this study, the elastic modulus, strength and Poisson ratio of warm frozen soil were measured, and the statistical characteristics under different temperature conditions are obtained. The autocorrelation distance (ACD) and autocorrelation function (ACF) of uncertain mechanical properties are estimated by random field (RF) method. The results show that the mean elastic modulus and mean strength decrease with the increase of temperature while the mean Poisson ratio increases with the increase of temperature. The average values of the ACD for the elastic modulus, strength and Poisson ratio are 0.64m, 0.53m and 0.48m, respectively. The standard deviation of the ACD for the elastic modulus, strength and Poisson ratio are 0.03m, 0.07m and 0.03m, respectively. The ACFs of elastic modulus, strength and Poisson ratio decrease with the increase of ratio of local average distance and scale of fluctuation. The ACF of uncertain mechanical properties is different when the temperature is different. This study can improve our understanding of the spatial autocorrelation variations of uncertain geotechnical properties and provide a basis and reference for the uncertain settlement analysis of frozen soil foundation.

Text Mining Analysis of Customer Reviews on Public Service Robots: With a focus on the Guide Robot Cases (텍스트 마이닝을 활용한 공공기관 서비스 로봇에 대한 사용자 리뷰 분석 : 안내로봇 사례를 중심으로)

  • Hyorim Shin;Junho Choi;Changhoon Oh
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.787-797
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    • 2023
  • The use of service robots, particularly guide robots, is becoming increasingly prevalent in public institutions. However, there has been limited research into the interactions between users and guide robots. To explore the customer experience with the guidance robot, we selected 'QI', which has been meeting customers for the longest time, and collected all reviews since the service was launched in public institutions. By using text mining techniques, we identified the main keywords and user experience factors and examined factors that hinder user experience. As a result, the guide robot's functionality, appearance, interaction methods, and role as a cultural commentator and helper were key factors that influenced the user experience. After identifying hindrance factors, we suggested solutions such as improved interaction design, multimodal interface service design, and content development. This study contributes to the understanding of user experience with guide robots and provides practical suggestions for improvement.

Text mining analysis of terms and information on product names used in online sales of women's clothing (텍스트마이닝을 활용한 온라인 판매 여성 의류 상품명에 나타난 용어 및 정보분석)

  • Yeo Sun Kang
    • The Research Journal of the Costume Culture
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    • v.31 no.1
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    • pp.34-52
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    • 2023
  • In this study, text mining was conducted on the product names of skirts, pants, shirts/blouses, and dresses to analyze the characteristics of keywords appearing in online shopping product names. As a result of frequency analysis, the number of keywords that appeared 0.5% or more for each item was around 30, and the number of keywords that appeared 0.1% or more was around 150. The cumulative distribution rate of 150 terms was around 80%. Accordingly, information on 150 key terms was analyzed, from which item, clothing composition, and material information were the found to be the most important types of information (ranking in the top five of all items). In addition, fit and style information for skirts and pants and length information for skirts and dresses were also considered important information. Keywords representing clothing composition information were: banding, high waist, and split for skirts and pants; and V-neck, tie, long sleeves, and puff for shirts/blouses and dresses. It was possible to identify the current design characteristics preferred by consumers from this information. However, there were also problems with terminology that hindered the connection between sellers and consumers. The most common problems were the use of various terms with the same meaning and irregular use of Korean and English terms. However, as a result of using co-appearance frequency analysis, it can be interpreted that there is little intention for product exposure, so it is recommended to avoid it.