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Process mining based on patient waiting time: an application in health processes

INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2022年第5/6期18卷 240-254页

作者： Dogan, Onur Izmir Bakircay Univ Dept Ind Engn Izmir Turkey

Purpose Similar to many business processes, waiting times are also essential for health care processes, especially in obstetrics and gynecology outpatient department (GOD), because pregnant women may be affected by long waiting times. Since creating process models manually presents subjective and nonrealistic flows, this study aims to meet the need of an objective and realistic method. Design/methodology/approach In this study, the authors investigate time-related bottlenecks in both departments for different doctors by process mining. Process mining is a pragmatic analysis to obtain meaningful insights through event logs. It applies data mining techniques to business process management with more comprehensive perspectives. Process mining in this study enables to automatically create patient flows to compare considering each department and doctor. Findings The study concludes that average waiting times in the GOD are higher than obstetrics outpatient department. However, waiting times in departments can change inversely for different doctors. Research limitations/implications The event log was created by expert opinions because activities in the processes had just starting timestamp. The ending time of activity was computed by considering the average duration of the corresponding activity under a normal distribution. Originality/value This study focuses on administrative (nonclinical) health processes in obstetrics and GOD. It uses a parallel activity log inference algorithm (PALIA) to produce process trees by handling duplicate activities. Infrequent information in health processes can have critical information about the patient. PALIA considers infrequent activities in the event log to extract meaningful information, in contrast to many discovery algorithms.

关键词： advanced web applications E-business models and architectures E-business application case studies Process mining Obstetrics and gynecology Time-related bottlenecks Patient behaviors Health care processes

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An execution environment as a service for adaptive long-running workflows

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2021年第2期17卷 117-139页

作者： Souza-Junior, Milton Secundino de Rosa, Nelson Souto Lins, Fernando Antonio Aires Univ Fed Pernambuco Ctr Informat Recife PE Brazil Univ Fed Rural Pernambuco Dept Computacao Recife PE Brazil

Purpose This paper aims to present Long4Cloud (long-running workflows execution environment for cloud), a distributed and adaptive LRW execution environment delivered "as a service" solution. Design/methodology/approach LRWs last for hours, days or even months and their duration open the possibility of changes in business rules, service interruptions or even alterations of formal regulations of the business before the workflow completion. These events can lead to problems such as loss of intermediary results or exhaustion of computational resources used to manage the workflow execution. Existing solutions face those problems by merely allowing the replacement (at runtime) of services associated with activities of the LRW. Findings LONG4Cloud extends the previous works in two main aspects, namely, the inclusion of dynamic reconfiguration capabilities and the adoption of an "as a service" delivery mode. The reconfiguration mechanism uses quiescence principles, data and state management and provides multiple adaptive strategies. Long4Cloud also adopts a scenario-based analysis to decide the adaptation to be performed. Events such as changes in business rules or service failures trigger reconfigurations supported by the environment. These features have been put together in a solution delivered "as a service" that takes advantage of cloud elasticity and allows to better allocate cloud resources to fit into the demands of LRWs. Originality/value The original contribution of Long4Cloud is to incorporate adaptive capabilities into the LRW execution environment as an effective way to handle the specificities of this kind of workflow. Experiments using current data of a Brazilian health insurance company were carried out to evaluate Long4Cloud and show performance gains in the execution of LRWs submitted to the proposed environment.

关键词： advanced web applications E-business models and architectures Workflow architectures in support of collaboration process Long-running workflow Business process automation Adaptive systems Service-oriented computing Cloud computing

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Click models inspired learning to rank

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2021年第4期17卷 261-286页

作者： Keyhanipour, Amir Hosein Oroumchian, Farhad Univ Tehran Comp Engn Dept Fac Engn Coll Farabi Tehran Iran Univ Wollongong Fac Engn & Informat Sci Dubai Knowledge Pk Dubai U Arab Emirates

Purpose Incorporating users' behavior patterns could help in the ranking process. Different click models (CMs) are introduced to model the sophisticated search-time behavior of users among which commonly used the triple of attractiveness, examination and satisfaction. Inspired by this fact and considering the psychological definitions of these concepts, this paper aims to propose a novel learning to rank by redefining these concepts. The attractiveness and examination factors could be calculated using a limited subset of information retrieval (IR) features by the random forest algorithm, and then they are combined with each other to predicate the satisfaction factor which is considered as the relevance level. Design/methodology/approach The attractiveness and examination factors of a given document are usually considered as its perceived relevance and the fast scan of its snippet, respectively. Here, attractiveness and examination factors are regarded as the click-count and the investigation rate, respectively. Also, the satisfaction of a document is supposed to be the same as its relevance level for a given query. This idea is supported by the strong correlation between attractiveness-satisfaction and the examination-satisfaction. Applying random forest algorithm, the attractiveness and examination factors are calculated using a very limited set of the primitive features of query-document pairs. Then, by using the ordered weighted averaging operator, these factors are aggregated to estimate the satisfaction. Findings Experimental results on MSLR-web10K and WCL2R data sets show the superiority of this algorithm over the state-of-the-art ranking algorithms in terms of P@n and NDCG criteria. The enhancement is more noticeable in top-ranked items which are reviewed more by the users. Originality/value This paper proposes a novel learning to rank based on the redefinition of major building blocks of the CMs which are the attractiveness, examination and satisfactory. It

关键词： advanced web applications web mining web search and information extraction Learning to rank Click models Random forest Information fusion

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A novel approach to diagnose ADHD using virtual reality

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2021年第5期17卷 516-536页

作者： Son, Ha Min Lee, Dong Gyu Joung, Yoo-Sook Lee, Ji Woo Seok, Eun Ju Chung, Tai-Myoung Oh, Soohwan Sungkyunkwan Univ Coll Comp Dept Comp Sci & Engn Suwon South Korea Samsung Med Ctr Dept Psychiat Seoul South Korea Sungkyunkwan Univ Sch Med Dept Psychiat Seoul South Korea Samsung Changwon Hosp Dept Psychiat Chang Won South Korea

Purpose The current golden standard for attention deficit hyperactivity disorder (ADHD) diagnosis is clinical diagnosis based on psychiatric interviews and psychological examinations. This is suboptimal, as clinicians are unable to view potential patients in multiple natural settings - a necessary condition for objective diagnosis. The purpose of this paper is to improve the objective diagnosis of ADHD by analyzing a quantified representation of the actions of potential patients in multiple natural environments. Design/methodology/approach The authors use both virtual reality (VR) and artificial intelligence (AI) to create an objective ADHD diagnostic test. Diagnostic and statistical manual of mental disorders, 5th Edition (DSM-5) and ADHD Rating Scale are used to create a rule-based system of quantifiable VR-observable actions. As a potential patient completes tasks within multiple VR scenes, certain actions trigger an increase in the severity measure of the corresponding ADHD symptom. The resulting severity measures are input to an AI model, which classifies the potential patient as having ADHD in the form inattention, hyperactivity-impulsivity, combined or neither. Findings The result of this study shows that VR-observed actions can be extracted as quantified data, and classification of this quantified data achieves near-perfect sensitivity and specificity with a 98.3% accuracy rate on a convolutional neural network model. Originality/value To the best of the authors' knowledge, this is the first study to incorporate VR and AI into an objective DSM-5-based ADHD diagnostic test. By including stimulation to the visual, auditory and equilibrium senses and tracking movement and recording voice, we present a method to further the research of objective ADHD diagnosis.

关键词： advanced web applications Migrating existing information web-based education

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Success prediction of crowdfunding campaigns: a two-phase modeling

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2020年第4期16卷 387-412页

作者： Silva, Lafaiet Silva, Nadia Felix Rosa, Thierson Univ Fed Goias Inst Informat Goiania Go Brazil

Purpose This study aims to analyze Kickstarter data along with social media data from a data mining perspective. Kickstarter is a crowdfunding financing plataform and is a form of fundraising and is increasingly being adopted as a source for achieving the viability of projects. Despite its importance and adoption growth, the success rate of crowdfunding campaigns was 47% in 2017, and it has decreased over the years. A way of increasing the chances of success of campaigns would be to predict, by using machine learning techniques, if a campaign would be successful. By applying classification models, it is possible to estimate if whether or not a campaign will achieve success, and by applying regression models, the authors can forecast the amount of money to be funded. Design/methodology/approach The authors propose a solution in two phases, namely, launching and campaigning. As a result, models better suited for each point in time of a campaign life cycle. Findings The authors produced a static predictor capable of classifying the campaigns with an accuracy of 71%. The regression method for phase one achieved a 6.45 of root mean squared error. The dynamic classifier was able to achieve 85% of accuracy before 10% of campaign duration, the equivalent of 3 days, given a campaign with 30 days of length. At this same period time, it was able to achieve a forecasting performance of 2.5 of root mean squared error. Originality/value The authors carry out this research presenting the results with a set of real data from a crowdfunding platform. The results are discussed according to the existing literature. This provides a comprehensive review, detailing important research instructions for advancing this field of literature.

关键词： Crowdfunding Classification Prediction Regression Machine learning Artificial intelligence advanced web applications web mining web search and information extraction

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Zeuss: a personalized tool for grammatical-construction learning

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2020年第1期16卷 1-22页

作者： Mendoza, Maria J. Velasco, David L. Moreno, Camilo A. Parra, Carlos Carrillo-Ramos, Angela Gomez-Morantes, Juan E. Pontificia Univ Javeriana Dept Syst & Comp Engn Bogota Colombia

Purpose The purpose of this paper is to present Zeuss, a software-based tool designed to improve grammar learning process in elementary school children. Despite efforts by the Colombian Government, the results of the final high school test indicate that students have major deficiencies with language, grammar and reading comprehension. Several difficulties have been evidenced in activities like writing essays or understanding academic papers. Among the reasons that may lead to these results include outdated courses, overcrowded classrooms and lack of interest. Design/methodology/approach A diagnostic test is performed on third-grade elementary school students to assess the current grammar knowledge and identify areas for improvement. The test results are used to design a software-based tool called Zeuss. The authors include playful activities inspired by several pedagogic exercises found in the literature and personalization so that interaction is tailored to specific user preferences and tastes. Findings Zeuss has been tested with third-grade students of the Gimnasio Campestre San Francisco de Sales elementary school in Bogota, Colombia. The results show that using the tool leads to an overall improvement in the grammar construction learning process. Originality/value Zeuss features updated pedagogical strategies, playful activities and a personalization model to tailor the learning process and help in context. It also allows teachers to track individual and classroom progress.

关键词： advanced web applications Education Personalization web-based education Mobile computing for the internet Playful activities

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website traffic measurement and rankings: competitive intelligence tools examination

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2018年第4期14卷 423-437页

作者： Prantl, David Prantl, Martin Univ W Bohemia Plzen Czech Republic

Purpose The purpose of this paper is to examine and verify the competitive intelligence tools Alexa and Similarweb, which are broadly used for website traffic data estimation. Tested tools belong to the state of the art in this area. Design/methodology/approach The authors use quantitative approach. Research was conducted on a sample of Czech websites for which there are accurate traffic data values, against which the other data sets (less accurate) provided by Alexa and Similarweb will be compared. Findings The results show that neither tool can accurately determine the ranking of websites on the internet. However, it is possible to approximately determine the significance of a particular website. These results are useful for another research studies which use data from Alexa or Similarweb. Moreover, the results show that it is still not possible to accurately estimate website traffic of any website in the world. Research limitations/implications The limitation of the research lies in the fact that it was conducted solely in the Czech market. Originality/value Significant amount of research studies use data sets provided by Alexa and Similarweb. However, none of these research studies focus on the quality of the website traffic data acquired by Alexa or Similarweb, nor do any of them refer to other studies that would deal with this issue. Furthermore, authors describe approaches to measuring website traffic and based on the analysis, the possible usability of these methods is discussed.

关键词： advanced web applications Rankings webometrics Internet quality of service Internet traffic engineering Competitive intelligence tools website traffic

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MovRec: a personalized movie recommendation system for children based on online movie features

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2017年第4期13卷 445-470页

作者： Ng, Yiu-Kai Brigham Young Univ Dept Comp Sci Provo UT 84602 USA

Purpose - The purpose of this study is to suggest suitable movies for children among the various multimedia selections available these days. Multimedia have a significant impact on the social and psychological development of children who are often explored to inappropriate materials, including movies that are either accessible online or through other multimedia channels. Even though not all movies are bad, there are negative effects of offensive languages, violence and sexuality as exhibited in movies. Parents and guidance of children need all the help they can get to promote the healthy use of movies these days. Design/methodology/approach - To offer parents appropriate movies of interest to their youths, the authors have developed MovRec, a personalized movie recommender for children, which is designed to provide educational and suitable entertaining opportunities for children. MovRec determines the appealingness of a movie for a particular user based on its children-appropriate score computed by using the backpropagation model, pre-defined category using latent Dirichlet allocation, its predicted rating using matrix factorization and sentiments based on its users' reviews, which along with its like/dislike count and genres, yield the features considered by MovRec. MovRec combines these features by using the CombMNZ model to rank and recommend movies. Findings - The performance evaluation of MovRec clearly demonstrates its effectiveness and its recommended movies are highly regarded by its users. Originality/value - Unlike Amazon and other online movie recommendation systems, such as Common Sense Media, Internet Movie Database and TasteKid, MovRec is unique, as to the best of the authors' knowledge, MovRec is the first personalized children movie recommender.

关键词： Children advanced web applications web search and information extraction Movie Personalized recommendation

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Monitoring platform for the consumption of electricity in a home

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2017年第3期13卷 222-240页

作者： Janeth Lancheros-Cuesta, Diana Perez Lara, Diego Bueno Lopez, Maximiliano Marulanda Garcia, Geovanny Univ La Salle Bogota Colombia

Purpose - Nowadays, an extra consumption of electric energy in the Colombian houses is generated due to electric or electronic elements plugged into the electric network. This fact produces a cost overrun in the user's electricity bills. To reduce this extra cost, and also with a plus of reducing greenhouse gas emission, a monitoring system for the consumption of electric energy in a household will be designed and implemented to make electricity users realize how much money and energy is being wasted due to the unnecessary electric elements plugged into the network. This paper aims to show a monitoring system that allows the client to supervise the consumption of some appliances inside his/her home, remotely. It is also considered the HMI to be able to log in, choose the intervals of data and generate reports and graphics. The monitoring system is based on the integration of several technologies that are already used and implemented in houses and buildings, such as: measuring and treatment of data electronically using microcontrollers, Wi-Fi technology and dynamic graphic interface (website). Design/methodology/approach - The methodology consists of several tasks, starting from documentation of the variables, instrumentation and methods for getting to the solution;the first part of the methodology focuses on selecting the electric and/or electronic elements to be monitored, so the instrumentation is able to monitor. Then, the power stage was implemented in this stage to measure signals from the sensors while sensing the electric nodes are adjusted, so does the transmission and reception. In the third stage, the design information system was implemented;this is where the received data from the sensors are stored and managed for further organization and visualization. Activities included the following: Analysis of the model of use cases: Identification of actors and actions that are involved in the system. Server selection: Study of the different server to manage the

关键词： advanced web applications Energy consumption Monitoring system Smart sensor

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Detecting and presenting welcome-news for tourists from user reviews

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INTERNATIONAL JOURNAL OF web INFORMATION SYSTEMS 2017年第4期13卷 354-369页

作者： Nadamoto, Akiyo Sakai, Keigo Konan Univ Dept Intelligence & Informat Kobe Hyogo Japan Konan Univ Kobe Hyogo Japan

Purpose - Recently, people usually use the internet to obtain travel information, when they plan their travel. They especially want to obtain sightseeing spot information from reviews, but there are huge amounts of reviews of sightseeing spots. Users therefore cannot obtain important information from the reviews easily. As described herein, this paper aims to propose a system that automatically extracts and presents welcome news for sightseeing spots from reviews. This proposed Welcome-news is a "useful information" and "unexpected information" related to travel. Design/methodology/approach - The flow for extracting Welcome- news from reviews is simple: A user inputs a sightseeing spot about which to get information;the system obtains reviews of the sightseeing spot and divides each sentence into reviews;the system extracts sentences including Welcome- news keyword (s), and the sentences become useful information;the system extracts unexpected information from useful information based on clustering, and it becomes Welcome-news;and the system presents all Welcome- news to the user. Findings - This paper reports three findings: extraction of useful information for sightseeing spots based on Welcome- news keywords extracted by our experiment and using support vector machine (SVM);extraction of unexpected information for sightseeing spots by clustering;and automatic presentation of Welcome- news. Originality/value - Numerous studies have extracted information from reviews based on some keywords. This proposed extraction of Welcome- news for travel not only uses keywords but also clusters based on topics. Furthermore, the proposed keywords include general keywords and unique keywords. The former appears for all kinds of sightseeing spots. The latter appears only for sightseeing spot. The authors extracted general keywords manually, and unique keywords using SVM.

关键词： advanced web applications applications of web mining and searching Migrating existing information

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