Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00071
Seiko Masuda, K. Ishigaki, H. Nishimura
Information education in the nursing profession has emphasized statistical processing. The content is not desirable to foster an ability to perform activities under the ongoing data health plan in Japan. For that reason, in this study, we aimed at developing a curriculum that incorporates a data health perspective for nursing college students, putting it into practice, and evaluating the results. As a result, it was confirmed that students' awareness and skills on data health response ability were improved.
{"title":"Informatics Curriculum for Nursing College Students According to the Data Health Perspective","authors":"Seiko Masuda, K. Ishigaki, H. Nishimura","doi":"10.1109/IIAI-AAI.2019.00071","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00071","url":null,"abstract":"Information education in the nursing profession has emphasized statistical processing. The content is not desirable to foster an ability to perform activities under the ongoing data health plan in Japan. For that reason, in this study, we aimed at developing a curriculum that incorporates a data health perspective for nursing college students, putting it into practice, and evaluating the results. As a result, it was confirmed that students' awareness and skills on data health response ability were improved.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132568316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00152
Yusuke Sato, Nobuyuki Kobayashi, S. Shirasaka
Rapid economic changes have recently been requesting human resource departments in Japanese firms to transform their roles and services. [1] No paper refers a method to map the themes they talk about and to discuss these issues explicitly by using the Harvard Model and Organization Strategy and Management Type. In this paper, we propose a method using the Harvard Model and Organization Strategy and Management Type. The method is divided into Visualization Map of HR Systems based on Life Cycle and Organization Strategy and Management Type. We asked employees of Human Resource Departments to use worksheets of "visualization map of HR systems based on life cycle" and "Organization Strategy and Management Type". Then, we evaluated the two points on whether they thought the HR System of their company was appropriate and whether they could write down and explain the HR System to other people. As a result, we confirmed that we achieved the goal of identifying issues of the firm and facilitating discussions with management and HR employees of other companies. In addition, this method could play a role in a training program for people who have a little experience as employees of Human Resource Departments.
{"title":"A Proposal of HR System's Visualization Based on Harvard Model, Life Cycle, and Organization Strategy and Management Type","authors":"Yusuke Sato, Nobuyuki Kobayashi, S. Shirasaka","doi":"10.1109/IIAI-AAI.2019.00152","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00152","url":null,"abstract":"Rapid economic changes have recently been requesting human resource departments in Japanese firms to transform their roles and services. [1] No paper refers a method to map the themes they talk about and to discuss these issues explicitly by using the Harvard Model and Organization Strategy and Management Type. In this paper, we propose a method using the Harvard Model and Organization Strategy and Management Type. The method is divided into Visualization Map of HR Systems based on Life Cycle and Organization Strategy and Management Type. We asked employees of Human Resource Departments to use worksheets of \"visualization map of HR systems based on life cycle\" and \"Organization Strategy and Management Type\". Then, we evaluated the two points on whether they thought the HR System of their company was appropriate and whether they could write down and explain the HR System to other people. As a result, we confirmed that we achieved the goal of identifying issues of the firm and facilitating discussions with management and HR employees of other companies. In addition, this method could play a role in a training program for people who have a little experience as employees of Human Resource Departments.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132125852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00135
Yoshiyuki Suimon, Hiroki Sakaji, T. Shimada, K. Izumi, Hiroyasu Matsushima
In recent years, overseas financial system crises (e.g., Lehman shock and European debt crisis) and the effects of monetary policy changes by US and European central banks exerted major influence on the Japanese interest rates market. In this research, we developed a forecasting model of Japanese interest rate based on a variety of machine learning methods, by considering the information obtained from overseas rates markets and currency markets. Finally, we confirmed that the prediction accuracy of Japanese long-term interest rate improved by using the US interest rates data in addition to the Japanese interest rates data for machine learning. Furthermore, we confirmed that the prediction accuracy increased by using US and Japanese rates markets data in recent years, particularly after 2006. This result suggests that information of overseas interest rates can be used to forecast Japanese rates market nowadays.
{"title":"Extraction of Relationship between Japanese and US Interest Rates using Machine Learning Methods","authors":"Yoshiyuki Suimon, Hiroki Sakaji, T. Shimada, K. Izumi, Hiroyasu Matsushima","doi":"10.1109/IIAI-AAI.2019.00135","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00135","url":null,"abstract":"In recent years, overseas financial system crises (e.g., Lehman shock and European debt crisis) and the effects of monetary policy changes by US and European central banks exerted major influence on the Japanese interest rates market. In this research, we developed a forecasting model of Japanese interest rate based on a variety of machine learning methods, by considering the information obtained from overseas rates markets and currency markets. Finally, we confirmed that the prediction accuracy of Japanese long-term interest rate improved by using the US interest rates data in addition to the Japanese interest rates data for machine learning. Furthermore, we confirmed that the prediction accuracy increased by using US and Japanese rates markets data in recent years, particularly after 2006. This result suggests that information of overseas interest rates can be used to forecast Japanese rates market nowadays.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122174303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00184
Toshinori Takai, Katsutoshi Shintani, Hideki Andoh, H. Washizaki
Developing an Internet of Things(IoT) application system has some challenges. For example, distinguishing the problem and solution domains is non-trivial in the developments and there are wide variations in the solution space to satisfy the given needs due to the nature of IoT systems. To deal with these problems, we propose an approach that integrates the GQM+Strategies method and the modeling language SysML for systems engineering. We also present a case study of the proposed approach and discuss future directions.
{"title":"Case Study Applying GQM+Strategies with SysML for IoT Application System Development","authors":"Toshinori Takai, Katsutoshi Shintani, Hideki Andoh, H. Washizaki","doi":"10.1109/IIAI-AAI.2019.00184","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00184","url":null,"abstract":"Developing an Internet of Things(IoT) application system has some challenges. For example, distinguishing the problem and solution domains is non-trivial in the developments and there are wide variations in the solution space to satisfy the given needs due to the nature of IoT systems. To deal with these problems, we propose an approach that integrates the GQM+Strategies method and the modeling language SysML for systems engineering. We also present a case study of the proposed approach and discuss future directions.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134457381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00201
Yulana Watanabe, T. Fujimoto
Today, many people have their own electronic devices, and use the internet. As a large part of the daily activities have now been digitized, many have no difficulty performing them by using the devices. Amid this digitization, a wide range of drawing software is evolving. From "drawing/painting" software that can be easily used by children and adults alike to those with specific features such as special software for product modeling and software with the texture of watercolor paints, different kinds of drawing software have been developed. Many creators and specialists use them which suit their purposes. While they all focus on providing functions and ease of use, few of the drawing software products represent realistic drawing experience. The sensation users have when working with analog tools creates emotional attachment to the tools. This leads to higher quality of the work and improved productivity. In addition, when drawing on paper with a pen or brush, unintended lines or points can be created. Though these cannot be easily corrected, they may add an intriguing touch to the work. With drawing software, this never happens, and making corrections is easy. In this research, we propose drawing software with realistic experience, which is one of the appeals of physical drawing as opposed to digitized drawing. In this paper, we focus on the realistic experience generated by sounds, and work on the sounds that vary by the combination of tools and materials.
{"title":"A Drawing Software that Changes User's Realistic Experience by Sounds Generated by the Combination of Tools and Materials","authors":"Yulana Watanabe, T. Fujimoto","doi":"10.1109/IIAI-AAI.2019.00201","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00201","url":null,"abstract":"Today, many people have their own electronic devices, and use the internet. As a large part of the daily activities have now been digitized, many have no difficulty performing them by using the devices. Amid this digitization, a wide range of drawing software is evolving. From \"drawing/painting\" software that can be easily used by children and adults alike to those with specific features such as special software for product modeling and software with the texture of watercolor paints, different kinds of drawing software have been developed. Many creators and specialists use them which suit their purposes. While they all focus on providing functions and ease of use, few of the drawing software products represent realistic drawing experience. The sensation users have when working with analog tools creates emotional attachment to the tools. This leads to higher quality of the work and improved productivity. In addition, when drawing on paper with a pen or brush, unintended lines or points can be created. Though these cannot be easily corrected, they may add an intriguing touch to the work. With drawing software, this never happens, and making corrections is easy. In this research, we propose drawing software with realistic experience, which is one of the appeals of physical drawing as opposed to digitized drawing. In this paper, we focus on the realistic experience generated by sounds, and work on the sounds that vary by the combination of tools and materials.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131941180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is well known that contributions from each learner's "collective cognitive responsibility" are essential in collaborative knowledge creation. This study examined whether real-time feedback can enhance collective cognitive responsibility. To consider this question, we hypothesized that attaining higher values of betweenness centrality in subjects' relationships reflects an improvement in collective cognitive responsibility; therefore, we developed a bulletin board system (BBS) to calculate values of betweenness centrality using network-analysis methodology in real-time. The research target was a student-staff community working for "Classroom-M" that used the BBS, which we called "HighNyammer," for information-sharing among students and staff members; it revealed the real-time value of betweenness centrality for each participant, based on relationships between the authors of posted articles. The results of this HighNyammer trial and a survey on four student-staff members demonstrated the potential effectiveness of this function, especially for novice workers. The value of betweenness centrality indicated each individual's position within the community.
{"title":"HighNyammer BBS Scaffolds the Development of Each Learner's Collective Cognitive Responsibility","authors":"Hideki Kondo, Sayaka Tohyama, Ayano Ohsaki, Masayuki Yamada","doi":"10.1109/IIAI-AAI.2019.00045","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00045","url":null,"abstract":"It is well known that contributions from each learner's \"collective cognitive responsibility\" are essential in collaborative knowledge creation. This study examined whether real-time feedback can enhance collective cognitive responsibility. To consider this question, we hypothesized that attaining higher values of betweenness centrality in subjects' relationships reflects an improvement in collective cognitive responsibility; therefore, we developed a bulletin board system (BBS) to calculate values of betweenness centrality using network-analysis methodology in real-time. The research target was a student-staff community working for \"Classroom-M\" that used the BBS, which we called \"HighNyammer,\" for information-sharing among students and staff members; it revealed the real-time value of betweenness centrality for each participant, based on relationships between the authors of posted articles. The results of this HighNyammer trial and a survey on four student-staff members demonstrated the potential effectiveness of this function, especially for novice workers. The value of betweenness centrality indicated each individual's position within the community.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132572790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00121
Yao-San Lin, Wan-Ni Cheng, C. Chen, Der-Chiang Li, Hung-Yu Chen
The small data learning issue has existed for over one hundred years (since 1908) when the Student's t-distribution was first developed. Few statistical tools can evaluate a population appropriately if the sample size is too small; small samples can be remedied through virtual sample generation (VSG) methods, which are widely used in industry and machine learning. However, most VSG methods were developed for data having only numerical attributes, very few studies have dealt with nominal attributes and cause domain estimation limitations. Therefore, this paper proposes a method that generates virtual samples based on the discrete degrees of nominal attributes, and then estimates the general population domains by fuzzy membership functions. A backpropagation neural network model and a support vector regression model are used to test the efficiency of the proposed method, while the Wilcoxon-sign test is used to test the difference with raw data sets. The result shows that the proposed method can reduce the mean absolute error and enhance classification accuracy by generating virtual samples that have nominal attributes.
{"title":"Generating Synthetic Samples to Improve Small Sample Learning with Mixed Numerical and Categorical Attributes","authors":"Yao-San Lin, Wan-Ni Cheng, C. Chen, Der-Chiang Li, Hung-Yu Chen","doi":"10.1109/IIAI-AAI.2019.00121","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00121","url":null,"abstract":"The small data learning issue has existed for over one hundred years (since 1908) when the Student's t-distribution was first developed. Few statistical tools can evaluate a population appropriately if the sample size is too small; small samples can be remedied through virtual sample generation (VSG) methods, which are widely used in industry and machine learning. However, most VSG methods were developed for data having only numerical attributes, very few studies have dealt with nominal attributes and cause domain estimation limitations. Therefore, this paper proposes a method that generates virtual samples based on the discrete degrees of nominal attributes, and then estimates the general population domains by fuzzy membership functions. A backpropagation neural network model and a support vector regression model are used to test the efficiency of the proposed method, while the Wilcoxon-sign test is used to test the difference with raw data sets. The result shows that the proposed method can reduce the mean absolute error and enhance classification accuracy by generating virtual samples that have nominal attributes.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132894797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00158
M. Teranishi, S. Matsumoto, Hidetoshi Takeno
The paper proposes an unsupervised classification method for peculiarities of flat finishing motion with an iron file, measured by a 3D stylus. The classified peculiarities are used to correct learner's finishing motions effectively for skill training. In the case of such skill training, the number of classes of peculiarity is unknown. A torus type Self-Organizing Maps(torus SOM) is effectively used to classify such unknown number of classes of peculiarity patterns. An automatic clustering method is applied to the torus SOM results based on cluster map value. Experimental results of the classification with measured data of an expert and sixteen learners show effectiveness of the proposed method. The effectiveness of the cluster map is also evaluated.
{"title":"Peculiarity Classification of Flat Finishing Skill Training by using Torus Type Self-Organizing Maps with Cluster Maps","authors":"M. Teranishi, S. Matsumoto, Hidetoshi Takeno","doi":"10.1109/IIAI-AAI.2019.00158","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00158","url":null,"abstract":"The paper proposes an unsupervised classification method for peculiarities of flat finishing motion with an iron file, measured by a 3D stylus. The classified peculiarities are used to correct learner's finishing motions effectively for skill training. In the case of such skill training, the number of classes of peculiarity is unknown. A torus type Self-Organizing Maps(torus SOM) is effectively used to classify such unknown number of classes of peculiarity patterns. An automatic clustering method is applied to the torus SOM results based on cluster map value. Experimental results of the classification with measured data of an expert and sixteen learners show effectiveness of the proposed method. The effectiveness of the cluster map is also evaluated.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133044460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00020
Genkou Ou, Kei Wakabayashi, T. Satoh
With the spread of the internet as social infrastructure, more and more people are shopping online. Online sites that formerly dealt with such specific products as books and clothing have also expanded to mall-type shopping sites by incorporating various kinds of stores. As a result, searching for products has become more complicated and prolonged. In this paper, we propose a method that models product-searching behavior based on the transition of the search words input by users. Since a query is generally composed of one or more search words, their information content is calculated in advance from query logs. Thus, varying the information content of the user's query sequences can be classified as a model of user searching behaviors. From analysis results using actual data, we confirmed that our proposed method effectively models product-searching behavior.
{"title":"Searching Behavior Analysis of Online Shopping Based on Information Content of Query Words","authors":"Genkou Ou, Kei Wakabayashi, T. Satoh","doi":"10.1109/IIAI-AAI.2019.00020","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00020","url":null,"abstract":"With the spread of the internet as social infrastructure, more and more people are shopping online. Online sites that formerly dealt with such specific products as books and clothing have also expanded to mall-type shopping sites by incorporating various kinds of stores. As a result, searching for products has become more complicated and prolonged. In this paper, we propose a method that models product-searching behavior based on the transition of the search words input by users. Since a query is generally composed of one or more search words, their information content is calculated in advance from query logs. Thus, varying the information content of the user's query sequences can be classified as a model of user searching behaviors. From analysis results using actual data, we confirmed that our proposed method effectively models product-searching behavior.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115332565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00028
Ya-Chu Chuang, Yung-Ming Li
With the rapid development of technology, the business model of the tourism industry has changed. More and more people need to rent the houses, and it is easier for customers to use and get information on the Internet. In the era of Web 2.0, consumers can leave rating scores and write reviews on the online social platforms to share their experience with others. Nonetheless, there may exist some spam reviews. In this paper, we propose a novel approach to detect user profiles and spam reviews so as to generate a rental house recommendation. With this new mechanism, consumers can receive an appropriate recommendation from their own basic information, preference, and their close friends or family who are with powerful influence on them. Also, with the support of the proposed mechanism, less fake or useless reviews influence them.
{"title":"Detecting Spam Reviews for Improving House Sharing Recommendation","authors":"Ya-Chu Chuang, Yung-Ming Li","doi":"10.1109/IIAI-AAI.2019.00028","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00028","url":null,"abstract":"With the rapid development of technology, the business model of the tourism industry has changed. More and more people need to rent the houses, and it is easier for customers to use and get information on the Internet. In the era of Web 2.0, consumers can leave rating scores and write reviews on the online social platforms to share their experience with others. Nonetheless, there may exist some spam reviews. In this paper, we propose a novel approach to detect user profiles and spam reviews so as to generate a rental house recommendation. With this new mechanism, consumers can receive an appropriate recommendation from their own basic information, preference, and their close friends or family who are with powerful influence on them. Also, with the support of the proposed mechanism, less fake or useless reviews influence them.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"384 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123195972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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