Pub Date : 2018-07-01DOI: 10.1109/JCSSE.2018.8457394
Surasak Tangsakul, S. Wongthanavasu
Hazy images are the images acquired under bad weather with low contrast and faint color properties. Several algorithms used dichromatic model to remove the haze in the image. This paper proposed a novel technique using cellular automata for the single image haze removal. It aims to improve the dark channel and the transmission map. We proposed the cellular automata rule to refine the intensity of image pixel in a dark channel. Then, the light source is estimated from the dark channel. Finally, we proposed the cellular automata rule to construct the transmission map and restored the haze-free image. The experimental results show that the proposed method improved intensity, color saturation quality, and avoid halo artifact without any post-processing when compared with the state-of-the-art methods.
{"title":"Improving Single Image Haze Removal Based On Cellular Automata Model","authors":"Surasak Tangsakul, S. Wongthanavasu","doi":"10.1109/JCSSE.2018.8457394","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457394","url":null,"abstract":"Hazy images are the images acquired under bad weather with low contrast and faint color properties. Several algorithms used dichromatic model to remove the haze in the image. This paper proposed a novel technique using cellular automata for the single image haze removal. It aims to improve the dark channel and the transmission map. We proposed the cellular automata rule to refine the intensity of image pixel in a dark channel. Then, the light source is estimated from the dark channel. Finally, we proposed the cellular automata rule to construct the transmission map and restored the haze-free image. The experimental results show that the proposed method improved intensity, color saturation quality, and avoid halo artifact without any post-processing when compared with the state-of-the-art methods.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127502369","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457366
Nattakarn Phaphoom, Wongduan Saelee, T. Somjaitaweeporn, Sumeth Yuenyong, Jian Qu
An enterprise resource planning (ERP) system offers vital capabilities to promote business competitiveness, operational excellence, and cost efficiency. Despite of advance in technology and research, enterprises are still struggling in the process of implementing and routinizing the use of ERP, as well as, achieving an optimal range of benefits it offers. The adoption challenges seem to be increasing in the context of developing countries where organizational cultures, attitude towards changes and ways of work are different than the context where ERP software was initiated. This study serves as a source of empirical evidences showing how ERP implementation can be carried out successfully for a SME manufacturing company in Thailand. The analysis was based on a series of in-depth interviews with the management, middle managers, and operational staffs of the company, which has integrated ERP to its enterprise processes and has enjoyed significant benefits of it for seven years. We combined qualitative analysis with a novel quantitative method called fuzzy weighting. Not only does the method offer better insight to the cases than the traditional approach, it also promotes internal validity of the analysis.
{"title":"A Combined Method for Analysing Critical Success Factors on ERP Implementation","authors":"Nattakarn Phaphoom, Wongduan Saelee, T. Somjaitaweeporn, Sumeth Yuenyong, Jian Qu","doi":"10.1109/JCSSE.2018.8457366","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457366","url":null,"abstract":"An enterprise resource planning (ERP) system offers vital capabilities to promote business competitiveness, operational excellence, and cost efficiency. Despite of advance in technology and research, enterprises are still struggling in the process of implementing and routinizing the use of ERP, as well as, achieving an optimal range of benefits it offers. The adoption challenges seem to be increasing in the context of developing countries where organizational cultures, attitude towards changes and ways of work are different than the context where ERP software was initiated. This study serves as a source of empirical evidences showing how ERP implementation can be carried out successfully for a SME manufacturing company in Thailand. The analysis was based on a series of in-depth interviews with the management, middle managers, and operational staffs of the company, which has integrated ERP to its enterprise processes and has enjoyed significant benefits of it for seven years. We combined qualitative analysis with a novel quantitative method called fuzzy weighting. Not only does the method offer better insight to the cases than the traditional approach, it also promotes internal validity of the analysis.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128099118","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457377
Sirisilp Kongsilp, Hathaichanok Chawmungkrung, T. Komuro
In this paper, we apply a Fish Tank Virtual Reality technique to a commodity tablet. Our first goal is to develop a tablet-based FTVR system that does not require additional enhancement to a tablet because it would allow tablet user to use the technology quickly and easily. To address this goal, we adopt a FTVR technique based on previous works and use it to develop our tablet FTVR prototype. It uses a camera-based face tracking and the anaglyph 3D display techniques. Our second goal is to determine that whether it is feasible to use tablet-based FTVR for entertainment and other mobile applications in daily life. To address the second goal, we implemented a game for our prototype called “pop-out Tetris Then we assess our prototype and the game using heuristic evaluation technique. We describe the technique that we used to develop our tablet FTVR prototype. The technique is based on previous works; it uses a camera-based face tracking and the anaglyph 3D display techniques. Therefore, it does not require any additional enhancement to a tablet. In addition to the prototype, we also implemented a game for tablet FTVR called “pop-out Tetris we describe our design of the application. Then we assess our prototype and the game using heuristic evaluation technique. In the end, we concluded that the technique is not ready for day-to-day use case scenario. We underline key points that affect the adoption of tablet-based FTVR technology and provide recommendations for future research to consider when developing a mobile FTVR system.
{"title":"Pop-Out Tetris: An Implementation of a Tablet FTVR Game","authors":"Sirisilp Kongsilp, Hathaichanok Chawmungkrung, T. Komuro","doi":"10.1109/JCSSE.2018.8457377","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457377","url":null,"abstract":"In this paper, we apply a Fish Tank Virtual Reality technique to a commodity tablet. Our first goal is to develop a tablet-based FTVR system that does not require additional enhancement to a tablet because it would allow tablet user to use the technology quickly and easily. To address this goal, we adopt a FTVR technique based on previous works and use it to develop our tablet FTVR prototype. It uses a camera-based face tracking and the anaglyph 3D display techniques. Our second goal is to determine that whether it is feasible to use tablet-based FTVR for entertainment and other mobile applications in daily life. To address the second goal, we implemented a game for our prototype called “pop-out Tetris Then we assess our prototype and the game using heuristic evaluation technique. We describe the technique that we used to develop our tablet FTVR prototype. The technique is based on previous works; it uses a camera-based face tracking and the anaglyph 3D display techniques. Therefore, it does not require any additional enhancement to a tablet. In addition to the prototype, we also implemented a game for tablet FTVR called “pop-out Tetris we describe our design of the application. Then we assess our prototype and the game using heuristic evaluation technique. In the end, we concluded that the technique is not ready for day-to-day use case scenario. We underline key points that affect the adoption of tablet-based FTVR technology and provide recommendations for future research to consider when developing a mobile FTVR system.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128471235","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457397
Panida Wiriyachaiporn, Kankawee Chanasit, A. Suchato, P. Punyabukkana, E. Chuangsuwanich
This paper presents the application of Machine Learning (ML) algorithm as an algorithmic music composer, compared to a rule-based algorithm. The ML model is based on LSTMs which takes in previous notes and predicts the next set of notes based on a midi format. For the rule-based method, we apply chord progression rules and binary rhythm pattern theory. We used both algorithms to generate music in two different genres, namely rock, and jazz. To evaluate the effectiveness of the algorithms, fifteen raters are asked to identify the genre of the generated songs. The results showed 77.33% of the rulebased algorithms Jazz songs were correctly identified, compared to the 62.67% generated by the LSTM. For the rock genre, only 49.33% percent of rule-based algorithms songs and 44% Machine Learning algorithms songs were correctly identified. In terms of music satisfaction, the rule-based algorithm on average obtains higher scores in both genres, 2.17 for Jazz and 2.42 for Rock while Machine Learning algorithm receives 1.83 for Jazz songs and 1.57 for Rock.
{"title":"Algorithmic Music Composition Comparison","authors":"Panida Wiriyachaiporn, Kankawee Chanasit, A. Suchato, P. Punyabukkana, E. Chuangsuwanich","doi":"10.1109/JCSSE.2018.8457397","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457397","url":null,"abstract":"This paper presents the application of Machine Learning (ML) algorithm as an algorithmic music composer, compared to a rule-based algorithm. The ML model is based on LSTMs which takes in previous notes and predicts the next set of notes based on a midi format. For the rule-based method, we apply chord progression rules and binary rhythm pattern theory. We used both algorithms to generate music in two different genres, namely rock, and jazz. To evaluate the effectiveness of the algorithms, fifteen raters are asked to identify the genre of the generated songs. The results showed 77.33% of the rulebased algorithms Jazz songs were correctly identified, compared to the 62.67% generated by the LSTM. For the rock genre, only 49.33% percent of rule-based algorithms songs and 44% Machine Learning algorithms songs were correctly identified. In terms of music satisfaction, the rule-based algorithm on average obtains higher scores in both genres, 2.17 for Jazz and 2.42 for Rock while Machine Learning algorithm receives 1.83 for Jazz songs and 1.57 for Rock.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121388030","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457331
Nattachai Tretasayuth, P. Vateekul, P. Boonkwan
Machine reading comprehension (MC) is one of the most important problems in natural language processing. Most of the previous works rely heavily on features engineering and handcrafting techniques. Since the release of SQuAD, a large-scale MC dataset, many deep learning models have been proposed. However, these models are limited by the soft attention mechanism only relied on keywords that appears in a question. Therefore, the performance is always poor in a question that needs to infer an answer from multiple sentences, which cannot depend on keywords in a question. In this paper, we propose a deep learning model that incorporates coreference information to improve the prediction performance especially on multiple sentence question. We also propose the bi-directional answering technique that can help the model avoid a local maxima of the single directional answering method in a traditional model. The results have shown that our approach outperforms the baseline in terms of F1 and Exact Match (EM).
{"title":"Enhance Machine Reading Comprehension on Multiple Sentence Questions with Gated and Dense Coreference Information","authors":"Nattachai Tretasayuth, P. Vateekul, P. Boonkwan","doi":"10.1109/JCSSE.2018.8457331","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457331","url":null,"abstract":"Machine reading comprehension (MC) is one of the most important problems in natural language processing. Most of the previous works rely heavily on features engineering and handcrafting techniques. Since the release of SQuAD, a large-scale MC dataset, many deep learning models have been proposed. However, these models are limited by the soft attention mechanism only relied on keywords that appears in a question. Therefore, the performance is always poor in a question that needs to infer an answer from multiple sentences, which cannot depend on keywords in a question. In this paper, we propose a deep learning model that incorporates coreference information to improve the prediction performance especially on multiple sentence question. We also propose the bi-directional answering technique that can help the model avoid a local maxima of the single directional answering method in a traditional model. The results have shown that our approach outperforms the baseline in terms of F1 and Exact Match (EM).","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130369339","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}
environmental awareness has been concerned as the primary factor for environmental sustainability. It can be said that people, especially young adults, should be educated to concern and aware of environmental protection. This paper addresses how to stimulate people to taking care of tree and plant by proposing a game-based learning system for plant monitoring based on Internet of Thing (IoT) technology. A novel approach of harmonization between the three main components, namely, real plant caring, game-based learning, and IoT technology, are discussed and proposed. A developed game-based learning system has been introduced and the experimental study of learners’ satisfaction of applying the proposed game in practical use has been reported.
{"title":"A Game-Based Learning System for Plant Monitoring Based on IoT Technology","authors":"Preecha Tangworakitthaworn, Vachirawit Tengchaisri, Kanokwan Rungsuptaweekoon, Tanapat Samakit","doi":"10.1109/JCSSE.2018.8457332","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457332","url":null,"abstract":"environmental awareness has been concerned as the primary factor for environmental sustainability. It can be said that people, especially young adults, should be educated to concern and aware of environmental protection. This paper addresses how to stimulate people to taking care of tree and plant by proposing a game-based learning system for plant monitoring based on Internet of Thing (IoT) technology. A novel approach of harmonization between the three main components, namely, real plant caring, game-based learning, and IoT technology, are discussed and proposed. A developed game-based learning system has been introduced and the experimental study of learners’ satisfaction of applying the proposed game in practical use has been reported.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123781880","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457329
Piyapat Charoensawan, P. Sukanya, I. Shimizu
This paper aims to find an effective method for identifying colors of fabrics. We consider the following color naming models: Basic Color terms, ISCC-NBS Color system, Frery’s Color name, and Fractals Lab’s Ultimate color vocabulary. The appropriate color name is assigned for a fabric image by using seven types of minimum distance in RGB and HSV color models. Experiments are performed on S3 plain color fabric images. Results show that in general, the method of identifying fabric color name by using Frery’s color name model with the color similarity measure by Euclidean distance in RGB space gives the better result than the other methods. When we analyze in more details by classifying fabric images into three groups based on color saturation, we found that the effective methods for color naming are as follows: Frery’s color name model with the quadratic distance in HSV space works well for the group of low color saturation (96.23% accuracy). Frery’s color name model with Euclidean distance in RGB space works well for the group of medium color saturation (81.82% accuracy). And Fractals Lab’s Ultimate color vocabulary model with the weighted Euclidean distance in HSV space work good for the group of high color saturation (76.09% accuracy).
{"title":"Comparison of Fabric Color Naming Using RGB and HSV Color Models","authors":"Piyapat Charoensawan, P. Sukanya, I. Shimizu","doi":"10.1109/JCSSE.2018.8457329","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457329","url":null,"abstract":"This paper aims to find an effective method for identifying colors of fabrics. We consider the following color naming models: Basic Color terms, ISCC-NBS Color system, Frery’s Color name, and Fractals Lab’s Ultimate color vocabulary. The appropriate color name is assigned for a fabric image by using seven types of minimum distance in RGB and HSV color models. Experiments are performed on S3 plain color fabric images. Results show that in general, the method of identifying fabric color name by using Frery’s color name model with the color similarity measure by Euclidean distance in RGB space gives the better result than the other methods. When we analyze in more details by classifying fabric images into three groups based on color saturation, we found that the effective methods for color naming are as follows: Frery’s color name model with the quadratic distance in HSV space works well for the group of low color saturation (96.23% accuracy). Frery’s color name model with Euclidean distance in RGB space works well for the group of medium color saturation (81.82% accuracy). And Fractals Lab’s Ultimate color vocabulary model with the weighted Euclidean distance in HSV space work good for the group of high color saturation (76.09% accuracy).","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130014064","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457181
Yusuke Katoh, Hironari Yoshiuchi, Yoshio Murata, H. Nakajo
We propose the Scalable Hardware Mechanism, which enables the operation of a partitioned circuit to prevent the degradation of clock frequency by minimizing its dependence on the usage and the type of FPGA. Our mechanism provides a reduced delay by the collective signal transmission with the partitioned AES code generation circuit and the character string edit distance calculation circuit as partitioned circuits. The collective signal transmission has attained 1.27 times improvement in the speed for the AES code generation circuit and 3.16 times improvement for the character string edit distance calculation circuit compared with the circuit by the conventional method.
{"title":"Operation in Partitioned Circuits with Scalable Hardware Mechanism","authors":"Yusuke Katoh, Hironari Yoshiuchi, Yoshio Murata, H. Nakajo","doi":"10.1109/JCSSE.2018.8457181","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457181","url":null,"abstract":"We propose the Scalable Hardware Mechanism, which enables the operation of a partitioned circuit to prevent the degradation of clock frequency by minimizing its dependence on the usage and the type of FPGA. Our mechanism provides a reduced delay by the collective signal transmission with the partitioned AES code generation circuit and the character string edit distance calculation circuit as partitioned circuits. The collective signal transmission has attained 1.27 times improvement in the speed for the AES code generation circuit and 3.16 times improvement for the character string edit distance calculation circuit compared with the circuit by the conventional method.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131499426","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457341
Narongsak Sukma, R. Chokngamwong
Nowadays, verifying the owner of every phone number is still possible only by showing the phone number on the screen. The telephone networks today do not have a proper validation process. This is a critical vulnerability for attackers to use this vulnerability to fake a phone number to deceive themselves as someone, i.e., a government agency and trick people into believing and eventually transferring money. Based on this problem, the research team has researched and found that many kinds of research have tried to solve the problem using a short message. (SMS), time spent on user response, hardware usage, and digital signature verification. However, the research team presented a new conceptual model as a onetime password authentication model for authentication. This new approach can reduce the need for external hardware, learning time and response time without the use of an external CA or a certification authority. This paper base on our previous paper [1] has a point that needed for improvement in the first time verification process. We propose a model that adds the ability to the first verification called advisory system which uses statistics to assist responsiveness to unknown calls. The testing result has shown the presence of fraud detection at the first call. The performance of the system is satisfied because the mobile phone that has this monitoring system installed still usually operates. Temperature, resources usage, and power consumption are not affected.
{"title":"Increasing the efficiency of One-time key Issuing for The First Verification Caller ID Spoofing Attacks","authors":"Narongsak Sukma, R. Chokngamwong","doi":"10.1109/JCSSE.2018.8457341","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457341","url":null,"abstract":"Nowadays, verifying the owner of every phone number is still possible only by showing the phone number on the screen. The telephone networks today do not have a proper validation process. This is a critical vulnerability for attackers to use this vulnerability to fake a phone number to deceive themselves as someone, i.e., a government agency and trick people into believing and eventually transferring money. Based on this problem, the research team has researched and found that many kinds of research have tried to solve the problem using a short message. (SMS), time spent on user response, hardware usage, and digital signature verification. However, the research team presented a new conceptual model as a onetime password authentication model for authentication. This new approach can reduce the need for external hardware, learning time and response time without the use of an external CA or a certification authority. This paper base on our previous paper [1] has a point that needed for improvement in the first time verification process. We propose a model that adds the ability to the first verification called advisory system which uses statistics to assist responsiveness to unknown calls. The testing result has shown the presence of fraud detection at the first call. The performance of the system is satisfied because the mobile phone that has this monitoring system installed still usually operates. Temperature, resources usage, and power consumption are not affected.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131637267","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457349
Ekapop Verasakulvong, P. Vateekul, Apivadee Piyatumrong, Chatchawal Sangkeettrakarn
Social media is one of the most impactful and fastest communication methods. By monitoring Twitter streams, we are able to detect emerging topics and understand events around the world. There are some prior attempts that aim to online detect topics on Twitter. However, they can only detect bursty topics by using user-defined keywords a long with simple rules. In this paper, we propose an algorithm to detect emerging topics on Twitter streams. To detect emerging topics, a clustering technique has been applied to aggregate a set of keywords. Since an emerging topic occurs continuously, the emerging topics are merged with stateful technique to accumulate topics from different time intervals. To detect both high signal topics and small-medium signal topics, we use statistical features based on average, acceleration, and z-score. Moreover, we propose to include the stock indicator features: Relative Strength Index (RSI) and Stochastic Oscillator (STOCH). They are common features in trend (oversold and overbought) detection in stock analysis which is similar to our topic detection in twitter. To capture any event patterns, Random Forest (RF) has been proposed as a classifier to detect emerging keywords by utilizing the stated above five features. To evaluate the performance, we created and published a corpus by collecting Twitter data for 10 days with over 80 million tweets and then labeling possible topics in tota1161 events along with related keywords. The experiment was conducted on our collected data. The Fl-results show that our model outperforms all baselines: TwitterMonitor, SigniTrend, and TopicSketch, in terms of detected keywords and topics.
{"title":"Online Emerging Topic Detection on Twitter Using Random Forest with Stock Indicator Features","authors":"Ekapop Verasakulvong, P. Vateekul, Apivadee Piyatumrong, Chatchawal Sangkeettrakarn","doi":"10.1109/JCSSE.2018.8457349","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457349","url":null,"abstract":"Social media is one of the most impactful and fastest communication methods. By monitoring Twitter streams, we are able to detect emerging topics and understand events around the world. There are some prior attempts that aim to online detect topics on Twitter. However, they can only detect bursty topics by using user-defined keywords a long with simple rules. In this paper, we propose an algorithm to detect emerging topics on Twitter streams. To detect emerging topics, a clustering technique has been applied to aggregate a set of keywords. Since an emerging topic occurs continuously, the emerging topics are merged with stateful technique to accumulate topics from different time intervals. To detect both high signal topics and small-medium signal topics, we use statistical features based on average, acceleration, and z-score. Moreover, we propose to include the stock indicator features: Relative Strength Index (RSI) and Stochastic Oscillator (STOCH). They are common features in trend (oversold and overbought) detection in stock analysis which is similar to our topic detection in twitter. To capture any event patterns, Random Forest (RF) has been proposed as a classifier to detect emerging keywords by utilizing the stated above five features. To evaluate the performance, we created and published a corpus by collecting Twitter data for 10 days with over 80 million tweets and then labeling possible topics in tota1161 events along with related keywords. The experiment was conducted on our collected data. The Fl-results show that our model outperforms all baselines: TwitterMonitor, SigniTrend, and TopicSketch, in terms of detected keywords and topics.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129100449","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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