Pub Date : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00049
Shu-Han Chang, C. Yang, Chao-Cheng Chen, Lih-Shyang Chen
In the last two decades, the concept of student-centered learning and problem-based learning (PBL) have swept through the educational community in most of the advanced countries. In medical PBL education, traditionally in order to train the students to be able to diagnose a patient with certain symptoms, the training procedure is always very time-consuming and labor-intensive. In particular there are usually only very limited number of specialists in practice. In order to solve this problem, we have developed a web-based PBL training system for medical education. The system can emulate a real clinical case that enables students to go through each step of a diagnosis procedure in an attempt to diagnose and cure a patient's disease. We believe that the system can significantly improve the learning efficiency and effectiveness for medical education.
{"title":"A Medical PBL System for Clinical Diagnosis Training in Medical Education","authors":"Shu-Han Chang, C. Yang, Chao-Cheng Chen, Lih-Shyang Chen","doi":"10.1109/Ubi-Media.2019.00049","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00049","url":null,"abstract":"In the last two decades, the concept of student-centered learning and problem-based learning (PBL) have swept through the educational community in most of the advanced countries. In medical PBL education, traditionally in order to train the students to be able to diagnose a patient with certain symptoms, the training procedure is always very time-consuming and labor-intensive. In particular there are usually only very limited number of specialists in practice. In order to solve this problem, we have developed a web-based PBL training system for medical education. The system can emulate a real clinical case that enables students to go through each step of a diagnosis procedure in an attempt to diagnose and cure a patient's disease. We believe that the system can significantly improve the learning efficiency and effectiveness for medical education.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128141493","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00064
Tanomsak Wongmeekaew, S. Boonkirdram, Songgrod Phimphisan
This research we present wireless sensor networks (WSNs) for monitoring of water quality of the pond Tilapia. By using the NodeMCU module WiFi to receive and collects signals from the peripherals sensor consists of a water level, dissolved oxygen, temperature and pH sensor for a tilapia pond and sending the sensor wireless signals to the central control unit using a Raspberry Pi controller for processing, database and display of water quality through the online auto-monitoring. The results showed that WSNs for monitoring water quality can be stored the database and showed the status normal, cautious and irregularities of the water quality well.
{"title":"Wireless Sensor Network for Monitoring of Water Quality for Pond Tilapia","authors":"Tanomsak Wongmeekaew, S. Boonkirdram, Songgrod Phimphisan","doi":"10.1109/Ubi-Media.2019.00064","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00064","url":null,"abstract":"This research we present wireless sensor networks (WSNs) for monitoring of water quality of the pond Tilapia. By using the NodeMCU module WiFi to receive and collects signals from the peripherals sensor consists of a water level, dissolved oxygen, temperature and pH sensor for a tilapia pond and sending the sensor wireless signals to the central control unit using a Raspberry Pi controller for processing, database and display of water quality through the online auto-monitoring. The results showed that WSNs for monitoring water quality can be stored the database and showed the status normal, cautious and irregularities of the water quality well.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"65 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132678951","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00052
Peng-Wen Chen, Yung-Hui Chen, Yi-Hsien Wu
Recently, digital notice boards have demonstrated their Internet of Things (IoT)-ready advantage and competitiveness in message publishing environments (e.g., smart campus environments or bus stations). However, current digital notice applications do not capture the context of daily life usage behavior and scenarios, and input devices, boards, notices, and the experience of human beings are all separate. This paper proposes an interactive message exchange architecture based on the Message Queuing Telemetry Transport (MQTT) protocol that deeply involves users in the IoT process. In this design, users can post notices from handheld devices to any supported display device or social media through a topic naming mechanism based on a subscribe/publish (sub/pub) model. Users can decide which notice to address. Messages of interest to the user will be integrated into a personal knowledge base. This paper also provides a demonstration of an integrated system for a smart campus.
{"title":"Pushing the Digital Notice Board toward Ubiquitous Based on the Concept of the Internet of Everything","authors":"Peng-Wen Chen, Yung-Hui Chen, Yi-Hsien Wu","doi":"10.1109/Ubi-Media.2019.00052","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00052","url":null,"abstract":"Recently, digital notice boards have demonstrated their Internet of Things (IoT)-ready advantage and competitiveness in message publishing environments (e.g., smart campus environments or bus stations). However, current digital notice applications do not capture the context of daily life usage behavior and scenarios, and input devices, boards, notices, and the experience of human beings are all separate. This paper proposes an interactive message exchange architecture based on the Message Queuing Telemetry Transport (MQTT) protocol that deeply involves users in the IoT process. In this design, users can post notices from handheld devices to any supported display device or social media through a topic naming mechanism based on a subscribe/publish (sub/pub) model. Users can decide which notice to address. Messages of interest to the user will be integrated into a personal knowledge base. This paper also provides a demonstration of an integrated system for a smart campus.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123552531","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00066
Xiaowei Zhao, Shusheng Shen
ICT leadership of the school administrators is an important factor which would affect the school ICT development. However, theoretical research on ICT leadership training has been not common. Based on MOOC platform, this paper designed an ICT leadership online course, and discussed the learning behavior patterns of administrators in the course of learning the course. Besides, the learning behavior data generated in the MOOC platform was analyzed by content analysis and lag sequence analysis. This study found that the behavior of learning course content was the main learning behavior of learners, but this behavior had no significant relationship with other behaviors. Learners could actively participate in discussion in the forum, but the interaction was largely for the purpose of getting good grades. Active learners were always able to participate in unit tests repeatedly, submitted homework on time and carried out peer reviews, so as to obtain the certificate.
{"title":"Research on Behavior Patterns of School Administrators in the MOOC of ICT Leadership","authors":"Xiaowei Zhao, Shusheng Shen","doi":"10.1109/Ubi-Media.2019.00066","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00066","url":null,"abstract":"ICT leadership of the school administrators is an important factor which would affect the school ICT development. However, theoretical research on ICT leadership training has been not common. Based on MOOC platform, this paper designed an ICT leadership online course, and discussed the learning behavior patterns of administrators in the course of learning the course. Besides, the learning behavior data generated in the MOOC platform was analyzed by content analysis and lag sequence analysis. This study found that the behavior of learning course content was the main learning behavior of learners, but this behavior had no significant relationship with other behaviors. Learners could actively participate in discussion in the forum, but the interaction was largely for the purpose of getting good grades. Active learners were always able to participate in unit tests repeatedly, submitted homework on time and carried out peer reviews, so as to obtain the certificate.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124118542","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00059
Ya-Wen Teng, Chih-Hua Tai
In a large database, the top-k query is an important mechanism to retrieve the most valuable information for the users, which ranks data objects with a ranking function and reports the k objects with the highest scores. However, as an object usually has various scores in the real world, ranking objects without information loss becomes challenging. In this paper, we model the object with multiple scores as an uncertain data object, where the uncertainty of the object is captured by a distribution of the scores, and address a novel problem named Best-kTEAM query, which discovers the best team with k players for a composite competition consisting of several games each of which requires a distinct number of players. To tackle the problem, we develop a dynamic programming based approach TeamGen to generate all possible solutions. Then, we introduce the notion of skyline teams with the property that none of them has a higher aggregated probability to be the top one for all games against the others and propose a filtering approach SubsetFilter to fast retrieve candidate solutions. Furthermore, instead of TeamGen, two heuristic approaches IgnoreTeamGen and LimitTeamGen are proposed to attempt to obtain possible solutions with better efficiency. The simulation shows the superiority of Best-kTEAM query in a composite competition and the proposed algorithms outperform the baseline approaches.
{"title":"Forming the Best Team for a Composite Competition","authors":"Ya-Wen Teng, Chih-Hua Tai","doi":"10.1109/Ubi-Media.2019.00059","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00059","url":null,"abstract":"In a large database, the top-k query is an important mechanism to retrieve the most valuable information for the users, which ranks data objects with a ranking function and reports the k objects with the highest scores. However, as an object usually has various scores in the real world, ranking objects without information loss becomes challenging. In this paper, we model the object with multiple scores as an uncertain data object, where the uncertainty of the object is captured by a distribution of the scores, and address a novel problem named Best-kTEAM query, which discovers the best team with k players for a composite competition consisting of several games each of which requires a distinct number of players. To tackle the problem, we develop a dynamic programming based approach TeamGen to generate all possible solutions. Then, we introduce the notion of skyline teams with the property that none of them has a higher aggregated probability to be the top one for all games against the others and propose a filtering approach SubsetFilter to fast retrieve candidate solutions. Furthermore, instead of TeamGen, two heuristic approaches IgnoreTeamGen and LimitTeamGen are proposed to attempt to obtain possible solutions with better efficiency. The simulation shows the superiority of Best-kTEAM query in a composite competition and the proposed algorithms outperform the baseline approaches.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130993549","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00024
Yi-Zhen Lin, Kai-Hsiang Chen, Jen-Wei Huang
To improve the vocabulary ability is very important in language learning. Thus, if we can learn and remember a word very effectively, then we will be able to master a language more quickly. Therefore, many scholars began to propose related research. Due to the learning mechanism of human brain, sometimes when people learn a new knowledge they may forgot at a short time. In order to make the consideration more complete, after analyzing Hermann Ebbinghaus's forgetting curve experiment, we added two variables, one is the acceptance of each word by the same person, and the other is the ability of different people to remember vocabulary. With the above two parameters, we want to design a system to help user to review the vocabulary which may be forgetting before. The forgetting curve can be personalized, and it is more accurate to calculate the best time for each user to review the vocabulary.
{"title":"Improving the Vocabulary Learning by Personalized Proficiency","authors":"Yi-Zhen Lin, Kai-Hsiang Chen, Jen-Wei Huang","doi":"10.1109/Ubi-Media.2019.00024","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00024","url":null,"abstract":"To improve the vocabulary ability is very important in language learning. Thus, if we can learn and remember a word very effectively, then we will be able to master a language more quickly. Therefore, many scholars began to propose related research. Due to the learning mechanism of human brain, sometimes when people learn a new knowledge they may forgot at a short time. In order to make the consideration more complete, after analyzing Hermann Ebbinghaus's forgetting curve experiment, we added two variables, one is the acceptance of each word by the same person, and the other is the ability of different people to remember vocabulary. With the above two parameters, we want to design a system to help user to review the vocabulary which may be forgetting before. The forgetting curve can be personalized, and it is more accurate to calculate the best time for each user to review the vocabulary.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"67 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124099112","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00018
Enkhtogtokh Togootogtokh, Sunan Huang, W. L. Leong, Rodney Teo Swee Huat, G. Foresti, C. Micheloni, Niki Maritnel
The recent breakthrough of artificial intelligence (AI) in many fields has recently shown its impact on drone technology as well. However, most of the provided solutions either entirely rely on commercial software or provide a weak integration interface which denies the development of additional techniques. This leads us to propose a novel and efficient frame-work for the drone technology. Specifically, we introduce the multi-layer AI (MLAI) framework which allows easy integration of ad-hoc AI applications. To demonstrate the benefits of the proposed framework, we implemented deep learning models to track and detect objects based on MLAI.
{"title":"An Efficient Artificial Intelligence Framework for UAV Systems","authors":"Enkhtogtokh Togootogtokh, Sunan Huang, W. L. Leong, Rodney Teo Swee Huat, G. Foresti, C. Micheloni, Niki Maritnel","doi":"10.1109/Ubi-Media.2019.00018","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00018","url":null,"abstract":"The recent breakthrough of artificial intelligence (AI) in many fields has recently shown its impact on drone technology as well. However, most of the provided solutions either entirely rely on commercial software or provide a weak integration interface which denies the development of additional techniques. This leads us to propose a novel and efficient frame-work for the drone technology. Specifically, we introduce the multi-layer AI (MLAI) framework which allows easy integration of ad-hoc AI applications. To demonstrate the benefits of the proposed framework, we implemented deep learning models to track and detect objects based on MLAI.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129227786","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}
The number of traffic incidents involving motorcyclists is on the rise; consequently research has focused on analysis of the head motions of motorcyclists to determine their level of concentration on the road while driving. These studies used three-axis accelerometers in helmets to record the acceleration signals that are detected when motorcyclists move their heads and then analyzed these signals using machine learning. However, we found that these methods are not very effective for the following reasons: (1) battery and memory capacity constraints mean that helmet sensors cannot collect acceleration data frequently, so the results cannot completely present head motions. (2) When motorcyclists are riding, the acceleration data collected by the helmets not only include the acceleration data of motorcyclist head motions but also include the acceleration data of motorcycle movement, which creates difficulties for recognition. (3) Due to the volume constraints of helmets, we cannot install GPUs or large-capacity batteries, so more complex models or deep learning models cannot be directly used for head motion recognition. (4) Head motions are smaller than body or limb motions, and most head motions do not occur periodically, which makes recognition even more difficult. To overcome these issues, this study proposed a novel machine learning method combined with a fuzzy neural network to perform motorcyclist head motion recognition with low-frequency acceleration signals collected from helmets. Experiment simulations demonstrate the validity of the proposed method.
{"title":"Motorcyclists' Head Motions Recognition by Using the Smart Helmet with Low Sampling Rate","authors":"Yu-Ren Chen, Chang-Ming Tsai, K. Wong, Tzu-Chang Lee, Chee-Hoe Loh, Jia-Ching Ying, Yi-Chung Chen","doi":"10.1109/Ubi-Media.2019.00038","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00038","url":null,"abstract":"The number of traffic incidents involving motorcyclists is on the rise; consequently research has focused on analysis of the head motions of motorcyclists to determine their level of concentration on the road while driving. These studies used three-axis accelerometers in helmets to record the acceleration signals that are detected when motorcyclists move their heads and then analyzed these signals using machine learning. However, we found that these methods are not very effective for the following reasons: (1) battery and memory capacity constraints mean that helmet sensors cannot collect acceleration data frequently, so the results cannot completely present head motions. (2) When motorcyclists are riding, the acceleration data collected by the helmets not only include the acceleration data of motorcyclist head motions but also include the acceleration data of motorcycle movement, which creates difficulties for recognition. (3) Due to the volume constraints of helmets, we cannot install GPUs or large-capacity batteries, so more complex models or deep learning models cannot be directly used for head motion recognition. (4) Head motions are smaller than body or limb motions, and most head motions do not occur periodically, which makes recognition even more difficult. To overcome these issues, this study proposed a novel machine learning method combined with a fuzzy neural network to perform motorcyclist head motion recognition with low-frequency acceleration signals collected from helmets. Experiment simulations demonstrate the validity of the proposed method.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129037939","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00061
Y. J. Lin, Shein-Yung Cheng, Meng-Yen Tom Lin
Under the big wave of artificial intelligence, one kind of critical technology is chatbot, whose virtual identity can play an important role in a virtual community. By proposing the system model of an Internet community and its chatbots, this paper designs target-monitoring (TM) intelligent agent and applies in real learning community. For a learning community platform, the system outputs can be assessment outcomes and learning attitudes, which can be transformed to linguistic variables by fuzzification. Moreover, a learning chatbot is designed with three-layered structure: fuzzified status, decision table and generated sentence. For learning, certain teaching strategies can be coded in the decision table to make chatbot generate advice sentences to learners. To prove the idea, a chatbot structure for learning monitoring is implemented within LINE community, and a real learning experiment is carried out. Moreover, such chatbot and its community system structure can be not only used in learning; an extended experiment is planned to construct a TM agent for operation management.
{"title":"Target-Monitoring Learning Companion Design","authors":"Y. J. Lin, Shein-Yung Cheng, Meng-Yen Tom Lin","doi":"10.1109/Ubi-Media.2019.00061","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00061","url":null,"abstract":"Under the big wave of artificial intelligence, one kind of critical technology is chatbot, whose virtual identity can play an important role in a virtual community. By proposing the system model of an Internet community and its chatbots, this paper designs target-monitoring (TM) intelligent agent and applies in real learning community. For a learning community platform, the system outputs can be assessment outcomes and learning attitudes, which can be transformed to linguistic variables by fuzzification. Moreover, a learning chatbot is designed with three-layered structure: fuzzified status, decision table and generated sentence. For learning, certain teaching strategies can be coded in the decision table to make chatbot generate advice sentences to learners. To prove the idea, a chatbot structure for learning monitoring is implemented within LINE community, and a real learning experiment is carried out. Moreover, such chatbot and its community system structure can be not only used in learning; an extended experiment is planned to construct a TM agent for operation management.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114689632","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 : 2019-08-01DOI: 10.1109/Ubi-Media.2019.00023
A. Ochirbat, Timothy K. Shih, Chalothon Chootong, Worapot Sommool, W. Gunarathne
With the growing new technologies and a vast variety of different jobs available to students, it is not possible to educate students with all necessary skills that they will need for different potential jobs. However, a gap between student skills and industry expectations is needed to decrease. In order to help senior students for discovering skills which are required to their intended jobs in ICT industry and improving their missing skills, we generate and provide wiki-based books based on their intended job-skills. We use two datasets, ICT jobs in labor market and ACM Computer Science 2013 (CS2013) guideline. Skills are extracted from job descriptions and keywords are extracted from knowledge units of CS2013, then those are mapped into each other. Finally, wiki-contents are extracted by using the keywords and wiki-books are generated. We discuss preliminary results and demonstrate the proposed system.
{"title":"Automatic Book Generation by using ICT Job-Skills and Computing Curricula","authors":"A. Ochirbat, Timothy K. Shih, Chalothon Chootong, Worapot Sommool, W. Gunarathne","doi":"10.1109/Ubi-Media.2019.00023","DOIUrl":"https://doi.org/10.1109/Ubi-Media.2019.00023","url":null,"abstract":"With the growing new technologies and a vast variety of different jobs available to students, it is not possible to educate students with all necessary skills that they will need for different potential jobs. However, a gap between student skills and industry expectations is needed to decrease. In order to help senior students for discovering skills which are required to their intended jobs in ICT industry and improving their missing skills, we generate and provide wiki-based books based on their intended job-skills. We use two datasets, ICT jobs in labor market and ACM Computer Science 2013 (CS2013) guideline. Skills are extracted from job descriptions and keywords are extracted from knowledge units of CS2013, then those are mapped into each other. Finally, wiki-contents are extracted by using the keywords and wiki-books are generated. We discuss preliminary results and demonstrate the proposed system.","PeriodicalId":259542,"journal":{"name":"2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126283099","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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