Pub Date : 2020-12-01DOI: 10.1109/CSCI51800.2020.00054
Thanh-Huong Le
Text sentiment analysis is target-oriented, aiming to identify the opinion or attitude from a piece of natural language text toward topics or entities, whether it is negative, positive or neutral using natural language processing and computational methods. With the growth of the internet, numerous business websites have been deployed to support shopping products, booking services online as well as to allow online reviewing and commenting the services in forms of either business forums or social networks. Use of text sentiment analysis for automatically mining opinion from the feedbacks on such emerging internet platforms is not only useful for customers seeking for advice, but also necessary for business to study customers’ attitudes toward brands, products, services, or events, and has become an increasingly dominant trend in business strategic management. Current state-of-the-art approaches for text sentiment analysis include lexicon based and machine learning based methods. In this research, we proposed a method that utilizes deep learning with attention word embedding. We showed that our method outperformed popular lexicon and embedding based methods.
{"title":"An attention-based deep learning method for text sentiment analysis","authors":"Thanh-Huong Le","doi":"10.1109/CSCI51800.2020.00054","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00054","url":null,"abstract":"Text sentiment analysis is target-oriented, aiming to identify the opinion or attitude from a piece of natural language text toward topics or entities, whether it is negative, positive or neutral using natural language processing and computational methods. With the growth of the internet, numerous business websites have been deployed to support shopping products, booking services online as well as to allow online reviewing and commenting the services in forms of either business forums or social networks. Use of text sentiment analysis for automatically mining opinion from the feedbacks on such emerging internet platforms is not only useful for customers seeking for advice, but also necessary for business to study customers’ attitudes toward brands, products, services, or events, and has become an increasingly dominant trend in business strategic management. Current state-of-the-art approaches for text sentiment analysis include lexicon based and machine learning based methods. In this research, we proposed a method that utilizes deep learning with attention word embedding. We showed that our method outperformed popular lexicon and embedding based methods.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116908389","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00265
Hyo-Kyun Kim, Tae-Sun Chung
This paper introduces an improved ANN (All Nearest Neighbor) algorithm using the SCL (Standard Clustered Loop) algorithm to reduce the consumption of computing resources that can occur when searching for the data object nearest to the query object in the process of executing the algorithm. Additionally, a method to improve ANN algorithm is proposed. When the algorithm is executed, it is a situation in which the user finds a data object adjacent to the user. In this case, our technique applies the criteria set provided by users.
{"title":"All Nearest Neighbors Query Including Scores Road Network","authors":"Hyo-Kyun Kim, Tae-Sun Chung","doi":"10.1109/CSCI51800.2020.00265","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00265","url":null,"abstract":"This paper introduces an improved ANN (All Nearest Neighbor) algorithm using the SCL (Standard Clustered Loop) algorithm to reduce the consumption of computing resources that can occur when searching for the data object nearest to the query object in the process of executing the algorithm. Additionally, a method to improve ANN algorithm is proposed. When the algorithm is executed, it is a situation in which the user finds a data object adjacent to the user. In this case, our technique applies the criteria set provided by users.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131070713","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00332
Jacobus Gideon Ackermann, John Andrew van der Poll
Developments in formal- and mathematical logic; and computing the past couple of decades have paved the way for the automation of deductive reasoning. However, despite theoretical and technological advances in computing, the rapid growth in the search space for complex proofs where the reasoner explores the consequences of irrelevant information, remains problematic. The challenge of a combinatorial explosion of the search space can in many cases be addressed by heuristics. Consequently, in this paper we investigate the extent to which heuristics may usefully be applied in discharging complex set-theoretic proof obligations using the hybrid reasoning environment, Rodin/Event-B. On the strength of our experiments, we develop a set of heuristics to aid the theorem-proving environment in finding proofs for set-theoretic problems which could not be obtained using the default settings. A brief exposition of related work in this area is presented towards the end of the paper.
{"title":"Reasoning Heuristics for the Theorem-Proving Platform Rodin/Event-B","authors":"Jacobus Gideon Ackermann, John Andrew van der Poll","doi":"10.1109/CSCI51800.2020.00332","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00332","url":null,"abstract":"Developments in formal- and mathematical logic; and computing the past couple of decades have paved the way for the automation of deductive reasoning. However, despite theoretical and technological advances in computing, the rapid growth in the search space for complex proofs where the reasoner explores the consequences of irrelevant information, remains problematic. The challenge of a combinatorial explosion of the search space can in many cases be addressed by heuristics. Consequently, in this paper we investigate the extent to which heuristics may usefully be applied in discharging complex set-theoretic proof obligations using the hybrid reasoning environment, Rodin/Event-B. On the strength of our experiments, we develop a set of heuristics to aid the theorem-proving environment in finding proofs for set-theoretic problems which could not be obtained using the default settings. A brief exposition of related work in this area is presented towards the end of the paper.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131148194","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00019
Abdulaziz A. Alsulami, S. Zein-Sabatto
In recent years, there has been a rapid expansion in the development of Cyber-Physical Systems (CPS), which allows the physical components and the cyber components of a system to be fully integrated and interacted with each other and with the physical world. The commercial aviation industry is shifting towards Aviation Cyber-Physical Systems (ACPS) framework because it allows real-time monitoring and diagnostics, real-time data analytics, and the use of Artificial Intelligent technologies in decision making. Inevitably, ACPS is not immune to cyber-attacks due to integrating a network system, which introduces serious security threats. False Data Injection (FDI) attack is widely used against CPS. It is a serious threat to the integrity of the connected physical components. In this paper, we propose a novel security algorithm for detecting FDI attacks in the communication network of ACPS using Artificial Immune System (AIS). The algorithm was developed based on the negative selection approach. The negative selection algorithm is used to detect malicious network packets and drop them. Then, a Nonlinear Autoregressive Exogenous (NARX) network is used to predict packets that dropped by the negative selection algorithm. The developed algorithm was implemented and tested on a networked control system of commercial aircraft as an Aviation Cyber-physical system.
{"title":"Detection and Defense from False Data Injection Attacks In Aviation Cyber-Physical Systems Using Artificial Immune Systems","authors":"Abdulaziz A. Alsulami, S. Zein-Sabatto","doi":"10.1109/CSCI51800.2020.00019","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00019","url":null,"abstract":"In recent years, there has been a rapid expansion in the development of Cyber-Physical Systems (CPS), which allows the physical components and the cyber components of a system to be fully integrated and interacted with each other and with the physical world. The commercial aviation industry is shifting towards Aviation Cyber-Physical Systems (ACPS) framework because it allows real-time monitoring and diagnostics, real-time data analytics, and the use of Artificial Intelligent technologies in decision making. Inevitably, ACPS is not immune to cyber-attacks due to integrating a network system, which introduces serious security threats. False Data Injection (FDI) attack is widely used against CPS. It is a serious threat to the integrity of the connected physical components. In this paper, we propose a novel security algorithm for detecting FDI attacks in the communication network of ACPS using Artificial Immune System (AIS). The algorithm was developed based on the negative selection approach. The negative selection algorithm is used to detect malicious network packets and drop them. Then, a Nonlinear Autoregressive Exogenous (NARX) network is used to predict packets that dropped by the negative selection algorithm. The developed algorithm was implemented and tested on a networked control system of commercial aircraft as an Aviation Cyber-physical system.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131153767","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00122
Marina Villalba Carballo, Byeong Kil Lee
Deep neural networks (DNNs) have several technical issues on computational complexity, redundancy, and the parameter size – especially when applied in embedded devices. Among those issues, lots of parameters require high memory capacity which causes migration problem to embedded devices. Many pruning techniques are proposed to reduce the network size in deep neural networks, but there are still various issues that exist for applying pruning techniques to DNNs. In this paper, we propose a simple-yet-efficient scheme, accuracy-aware structured pruning based on the characterization of each convolutional layer. We investigate the accuracy and compression rate of individual layer with a fixed pruning ratio and re-order the pruning priority depending on the accuracy of each layer. To achieve a further compression rate, we also add quantization to the linear layers. Our results show that the order of the layers pruned does affect the final accuracy of the deep neural network. Based on our experiments, the pruned AlexNet and VGG16 models’ parameter size is compressed up to 47.28x and 35.21x with less than 1% accuracy drop with respect to the original model.
{"title":"Accuracy-aware Structured Filter Pruning for Deep Neural Networks","authors":"Marina Villalba Carballo, Byeong Kil Lee","doi":"10.1109/CSCI51800.2020.00122","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00122","url":null,"abstract":"Deep neural networks (DNNs) have several technical issues on computational complexity, redundancy, and the parameter size – especially when applied in embedded devices. Among those issues, lots of parameters require high memory capacity which causes migration problem to embedded devices. Many pruning techniques are proposed to reduce the network size in deep neural networks, but there are still various issues that exist for applying pruning techniques to DNNs. In this paper, we propose a simple-yet-efficient scheme, accuracy-aware structured pruning based on the characterization of each convolutional layer. We investigate the accuracy and compression rate of individual layer with a fixed pruning ratio and re-order the pruning priority depending on the accuracy of each layer. To achieve a further compression rate, we also add quantization to the linear layers. Our results show that the order of the layers pruned does affect the final accuracy of the deep neural network. Based on our experiments, the pruned AlexNet and VGG16 models’ parameter size is compressed up to 47.28x and 35.21x with less than 1% accuracy drop with respect to the original model.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132858440","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00179
Daniela Eloise Flôr, Eduardo Henrique Molina da Cruz, A. Possebom, Carlos Roberto Beleti Junior, Rodrigo Hübner, Linnyer Beatrys Ruiz Aylon
This case addresses the challenge of developing a novel educational strategy that promotes hard and soft skills using different types of emerging technologies. We achieved this with a horizontal collaborative learning strategy, between universities, and vertical collaborative learning, between universities and schools, organized by the MannaTeam network. In addition to sharing experiences, knowledge, laboratories and materials among network partners, we popularized our vision of education for the 21st century – Education 5.0, and invested in a project of female empowerment, showing society the reasons and impacts of the gender gap in technological areas. The success of our contemporary vision of education and the efforts of MannaTeam motivate us to continue. There is much to be done to stimulate innovation in education and the broad understanding that ability has no gender.
{"title":"MannaTeam: a case of interinstitutional collaborative learning and Education 5.0","authors":"Daniela Eloise Flôr, Eduardo Henrique Molina da Cruz, A. Possebom, Carlos Roberto Beleti Junior, Rodrigo Hübner, Linnyer Beatrys Ruiz Aylon","doi":"10.1109/CSCI51800.2020.00179","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00179","url":null,"abstract":"This case addresses the challenge of developing a novel educational strategy that promotes hard and soft skills using different types of emerging technologies. We achieved this with a horizontal collaborative learning strategy, between universities, and vertical collaborative learning, between universities and schools, organized by the MannaTeam network. In addition to sharing experiences, knowledge, laboratories and materials among network partners, we popularized our vision of education for the 21st century – Education 5.0, and invested in a project of female empowerment, showing society the reasons and impacts of the gender gap in technological areas. The success of our contemporary vision of education and the efforts of MannaTeam motivate us to continue. There is much to be done to stimulate innovation in education and the broad understanding that ability has no gender.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128078345","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00306
José Prades, A. Salazar, G. Safont, L. Vergara
Some applications require knowing how many materials are present in the scene represented by a hyperspectral Image. In a previous paper, we presented an algorithm that estimated the number of materials in the scene using clustering principles. The proposed algorithm obtains a hierarchy of image partitions and selects a partition using a validation Index; the estimated number of materials is set to the number of dusters of the selected partition. In this algorithm, the user must provide the Image and the maximum number of materials that can be estimated (P). In this paper, we have extended our algorithm so that It does not require P as input parameter. The proposed method Iteratively performs the estimation for several increasing values of P and stops the process when a certain condition is met. The results obtained with five hyperspectral Images show that our algorithm approximately estimates the number of materials in that images.
{"title":"Determining the number of endmembers of hyperspectral images using clustering","authors":"José Prades, A. Salazar, G. Safont, L. Vergara","doi":"10.1109/CSCI51800.2020.00306","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00306","url":null,"abstract":"Some applications require knowing how many materials are present in the scene represented by a hyperspectral Image. In a previous paper, we presented an algorithm that estimated the number of materials in the scene using clustering principles. The proposed algorithm obtains a hierarchy of image partitions and selects a partition using a validation Index; the estimated number of materials is set to the number of dusters of the selected partition. In this algorithm, the user must provide the Image and the maximum number of materials that can be estimated (P). In this paper, we have extended our algorithm so that It does not require P as input parameter. The proposed method Iteratively performs the estimation for several increasing values of P and stops the process when a certain condition is met. The results obtained with five hyperspectral Images show that our algorithm approximately estimates the number of materials in that images.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128384033","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00316
L. Deligiannidis
In this work we present an inexpensive, yet accurate, solution of measuring human temperature from a distance. The need for such solution is essential during pandemics. During COVID-19, one of the most common symptoms, for those who develop symptoms, is fever. We believe a tool that measures multiple peoples’ temperature from a safe distance can be valuable. As people enter buildings, airports, hospitals, etc. they can be scanned automatically from a safe distance. The system can alert the authorities for further assessment. Even though such a tool does not prevent the spread of a virus by itself, it can help contain the virus following additional measures such as wearing a face mask, frequent hand washing, and social distancing.
{"title":"Human Temperature Scanning from a Distance","authors":"L. Deligiannidis","doi":"10.1109/CSCI51800.2020.00316","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00316","url":null,"abstract":"In this work we present an inexpensive, yet accurate, solution of measuring human temperature from a distance. The need for such solution is essential during pandemics. During COVID-19, one of the most common symptoms, for those who develop symptoms, is fever. We believe a tool that measures multiple peoples’ temperature from a safe distance can be valuable. As people enter buildings, airports, hospitals, etc. they can be scanned automatically from a safe distance. The system can alert the authorities for further assessment. Even though such a tool does not prevent the spread of a virus by itself, it can help contain the virus following additional measures such as wearing a face mask, frequent hand washing, and social distancing.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128408152","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00236
Anil L. Pereira
In this paper, a data transfer, indexing and storage system on a commodity-off-the-shelf cluster using parallel processing, asynchronous file Input/Output, direct memory access and asynchronous User Datagram Protocol sockets is proposed. Also, a performance evaluation framework for the system is described. There are two main considerations in developing the system. First, as data communication networks support increased data rates due to fiber optical cables and more efficient network devices, better data transfer and storage methods are required to exploit the speed of the networks. Second, applications in particle physics, climate modeling and weapon systems simulation generate petabytes of data from a single experiment. The challenge is to index and store the data as soon as it is produced and preprocessed by several instruments.
{"title":"Parallel Data Indexing and Storage on a COTS Cluster","authors":"Anil L. Pereira","doi":"10.1109/CSCI51800.2020.00236","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00236","url":null,"abstract":"In this paper, a data transfer, indexing and storage system on a commodity-off-the-shelf cluster using parallel processing, asynchronous file Input/Output, direct memory access and asynchronous User Datagram Protocol sockets is proposed. Also, a performance evaluation framework for the system is described. There are two main considerations in developing the system. First, as data communication networks support increased data rates due to fiber optical cables and more efficient network devices, better data transfer and storage methods are required to exploit the speed of the networks. Second, applications in particle physics, climate modeling and weapon systems simulation generate petabytes of data from a single experiment. The challenge is to index and store the data as soon as it is produced and preprocessed by several instruments.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"05 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132096396","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 : 2020-12-01DOI: 10.1109/CSCI51800.2020.00049
Damián Martínez Díaz, Francisco LUNA ROSAS, Julio Cesar Martínez Romo, Marco Antonio Hernandez Vargas, Ivan CASTILLO ZUÑIGA
There is a suicide every 40 seconds in the world and it is the third cause of death for young people between 15 and 19 years old worldwide. For every suicide, many more attempt it, which is why suicide prevention remains an universal challenge and has been recognized by the World Health Organization (WHO) as a public health priority. Experts say that one of the best ways to prevent suicide is for people who are going through this urge to take their own lives to listen to people who are close to them and social networks such as Twitter or Facebook are in a unique position to help these people connect in real time in difficult situations that people with these suicidal tendencies are going through, but also represents a potential risk to receive information that could later prove harmful, either by stressing the same information or by taking some suicidal ideas. In this research we propose a model to optimize the global time processing in the detection of patterns related to suicide in the social network Twitter. Our results show that the proposed model can be a good alternative when it comes to optimizing the response time in this type of problems.
{"title":"Optimizing global processing time in the detection of patterns related to suicide in social networks","authors":"Damián Martínez Díaz, Francisco LUNA ROSAS, Julio Cesar Martínez Romo, Marco Antonio Hernandez Vargas, Ivan CASTILLO ZUÑIGA","doi":"10.1109/CSCI51800.2020.00049","DOIUrl":"https://doi.org/10.1109/CSCI51800.2020.00049","url":null,"abstract":"There is a suicide every 40 seconds in the world and it is the third cause of death for young people between 15 and 19 years old worldwide. For every suicide, many more attempt it, which is why suicide prevention remains an universal challenge and has been recognized by the World Health Organization (WHO) as a public health priority. Experts say that one of the best ways to prevent suicide is for people who are going through this urge to take their own lives to listen to people who are close to them and social networks such as Twitter or Facebook are in a unique position to help these people connect in real time in difficult situations that people with these suicidal tendencies are going through, but also represents a potential risk to receive information that could later prove harmful, either by stressing the same information or by taking some suicidal ideas. In this research we propose a model to optimize the global time processing in the detection of patterns related to suicide in the social network Twitter. Our results show that the proposed model can be a good alternative when it comes to optimizing the response time in this type of problems.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134055587","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：