Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090217
Hamza Osman Ilhan, C. Avci
In medical science, sleep stages are the main criteria to define the disorders and have crucial role on diagnostic. In this sense, accurate sleep stage classification plays important role due to provide better report on medications and diagnoses. In this study, EEG signals are classified by a rule based machine learning algorithm; Decision Tree with the ensemble and classical machine learning idea. Additionally, two of active sample selection technique using the idea of strictly separated discrimination and margin distances are applied on learning processes to obtain more accurate results with less samples. This paper proves that ensemble learning algorithms with one of the implemented active sample selection technique gives more successful result on the determination of stages.
{"title":"Sleep stage classification by ensemble learning methods with active sample selection techniques","authors":"Hamza Osman Ilhan, C. Avci","doi":"10.1109/IDAP.2017.8090217","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090217","url":null,"abstract":"In medical science, sleep stages are the main criteria to define the disorders and have crucial role on diagnostic. In this sense, accurate sleep stage classification plays important role due to provide better report on medications and diagnoses. In this study, EEG signals are classified by a rule based machine learning algorithm; Decision Tree with the ensemble and classical machine learning idea. Additionally, two of active sample selection technique using the idea of strictly separated discrimination and margin distances are applied on learning processes to obtain more accurate results with less samples. This paper proves that ensemble learning algorithms with one of the implemented active sample selection technique gives more successful result on the determination of stages.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127947311","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090176
Orhan Yaman, M. Karakose
Elevators are the means that people often use in everyday life. From the past until nowadays many elevators have been used in many areas. Elevator systems with the formation of high-rise buildings in recent years has become more important. Early diagnosis of faults that may occur in the elevator system is very important. In this study, an approach has been proposed to monitor and detect faults on elevator ropes. The proposed method is based on image processing and auto correlation. Images are taken with the cameras fixed to the elevator system. The position of the elevator rope is determined by extracting the edges on the images. Thus, the elevator rope is monitored in real time. The detected rope is cut off from the gray format image. The elevator rope is observed by applying auto correlation to the obtained image. It is converted into image signals by using auto correlation method. The difference signal is generated by using the obtained auto correlation signal. High values in the difference signal are detected as rope fault. The proposed fault detection approach is quite fast because it has a signal processing base.
{"title":"Auto correlation based elevator rope monitoring and fault detection approach with image processing","authors":"Orhan Yaman, M. Karakose","doi":"10.1109/IDAP.2017.8090176","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090176","url":null,"abstract":"Elevators are the means that people often use in everyday life. From the past until nowadays many elevators have been used in many areas. Elevator systems with the formation of high-rise buildings in recent years has become more important. Early diagnosis of faults that may occur in the elevator system is very important. In this study, an approach has been proposed to monitor and detect faults on elevator ropes. The proposed method is based on image processing and auto correlation. Images are taken with the cameras fixed to the elevator system. The position of the elevator rope is determined by extracting the edges on the images. Thus, the elevator rope is monitored in real time. The detected rope is cut off from the gray format image. The elevator rope is observed by applying auto correlation to the obtained image. It is converted into image signals by using auto correlation method. The difference signal is generated by using the obtained auto correlation signal. High values in the difference signal are detected as rope fault. The proposed fault detection approach is quite fast because it has a signal processing base.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116662741","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090185
Tolunay Göçken, M. Yaktubay, Fatih Kılıç
In this study, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a single depot and identical vehicles, is considered. Minimizing the total distance and the total waiting time of the vehicles are determined as objective functions for VRPTW which is capable to serve the customers in a prespecified time interval. A hybridized version of genetic algorithm which is a metaheuristic solution technique with constructive heuristic methods is proposed to produce effective solutions for VRPTW. By using sweep algorithm in initial population generation phase of genetic algorithm, it is planned to begin the search with high quality solution sets and in this way, get more feasible solutions faster. A benchmark problem in the literature is solved and obtained results are compared with the results of genetic algorithm with the nearest neighbor algorithm based algorithm. It is observed that the proposed genetic algorithm beginning with sweep based initial population generation algorithm reaches more effective solutions.
{"title":"Improvement of a genetic algorithm approach for the solution of vehicle routing problem with time windows","authors":"Tolunay Göçken, M. Yaktubay, Fatih Kılıç","doi":"10.1109/IDAP.2017.8090185","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090185","url":null,"abstract":"In this study, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a single depot and identical vehicles, is considered. Minimizing the total distance and the total waiting time of the vehicles are determined as objective functions for VRPTW which is capable to serve the customers in a prespecified time interval. A hybridized version of genetic algorithm which is a metaheuristic solution technique with constructive heuristic methods is proposed to produce effective solutions for VRPTW. By using sweep algorithm in initial population generation phase of genetic algorithm, it is planned to begin the search with high quality solution sets and in this way, get more feasible solutions faster. A benchmark problem in the literature is solved and obtained results are compared with the results of genetic algorithm with the nearest neighbor algorithm based algorithm. It is observed that the proposed genetic algorithm beginning with sweep based initial population generation algorithm reaches more effective solutions.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115630523","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090209
İslam Mayda, Mirsat Yesiltepe
Twitter is one of the most popular social media networks in the world. It is also mostly used by corporate companies, media as well as individual users. Media organizations use Twitter to announce about the news. Although the language of the given news is formal and preferred words to share information are different for each organization. In this study, we proposed an approach to recognize the Twitter accounts of Turkish daily newspapers. Our approach is based on character 3-grams and word 2-grams for digitizing the texts. In order to classify the information, we performed the experiments on several classifiers and found that Sequential Minimal Optimization (SMO) outperformed other algorithms. We carried out the experiments on the real-dataset of Twitter accounts of Turkish daily newspapers and classified them accurately more than 98%.1
{"title":"N-gram based approach to recognize the twitter accounts of Turkish daily newspapers","authors":"İslam Mayda, Mirsat Yesiltepe","doi":"10.1109/IDAP.2017.8090209","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090209","url":null,"abstract":"Twitter is one of the most popular social media networks in the world. It is also mostly used by corporate companies, media as well as individual users. Media organizations use Twitter to announce about the news. Although the language of the given news is formal and preferred words to share information are different for each organization. In this study, we proposed an approach to recognize the Twitter accounts of Turkish daily newspapers. Our approach is based on character 3-grams and word 2-grams for digitizing the texts. In order to classify the information, we performed the experiments on several classifiers and found that Sequential Minimal Optimization (SMO) outperformed other algorithms. We carried out the experiments on the real-dataset of Twitter accounts of Turkish daily newspapers and classified them accurately more than 98%.1","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125362809","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090167
Pelin Altinişik, Erhan Ergün
Bu çalişmada, görüntülerdeki tuz ve biber gürültüsünü gidermek için iki yeni yaklaşim önerilmektedir. Bu yaklaşimlar, özyinelemeli ortanca süzgeç (ÖOS) yöntemine dayalidirlar. Bundan dolayi, önerilen süzgeçler ÖOS2 ve ÖOS3 olarak adlandirilmaktadirlar. ÖOS2 ve ÖOS3, tuz ve biber gürültülü Lena görüntülerine uygulanmaktadirlar. Süzgeçlerin başarimlari, literatürde yer alan ortanca süzgeç (OS) ve ÖOS ile karşilaştirilmaktadir. Görsel ve nicel olarak elde edilen karşilaştirma sonuçlarina göre önerilen süzgeçlerin, diğer süzgeçlerden daha başarili olduğu görülmektedir.
{"title":"Özyinelemeli ortanca süzgeç İçin İki yeni yaklaşim","authors":"Pelin Altinişik, Erhan Ergün","doi":"10.1109/IDAP.2017.8090167","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090167","url":null,"abstract":"Bu çalişmada, görüntülerdeki tuz ve biber gürültüsünü gidermek için iki yeni yaklaşim önerilmektedir. Bu yaklaşimlar, özyinelemeli ortanca süzgeç (ÖOS) yöntemine dayalidirlar. Bundan dolayi, önerilen süzgeçler ÖOS2 ve ÖOS3 olarak adlandirilmaktadirlar. ÖOS2 ve ÖOS3, tuz ve biber gürültülü Lena görüntülerine uygulanmaktadirlar. Süzgeçlerin başarimlari, literatürde yer alan ortanca süzgeç (OS) ve ÖOS ile karşilaştirilmaktadir. Görsel ve nicel olarak elde edilen karşilaştirma sonuçlarina göre önerilen süzgeçlerin, diğer süzgeçlerden daha başarili olduğu görülmektedir.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125394018","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090184
A. Denker, M. İşeri
Humankind encounters with unprecedented number and scales of disasters which stem from natural and human-made causes. So many victims have suffered severely in those catastrophes that compelled generation and development of search and rescue technology to help victims in future. One of the most important application areas within this scope is the search and rescue robots. The robots equipped with capabilities of sensing and maneuvering in the areas of calamity are enticing more and more attentions from researchers and rescuers. This project aims at realization of a new generation of search and rescue robot which can work in autonomous and semi-autonomous modes and can be used in harsh physical environments of disaster regions to carry out the given tasks more effectively by the use of advanced and economic sensors. In this paper, a mobile search and rescue robot called SALVOR is designed and implemented. SALVOR partly relies on the data from its sensors about the environment and partly on instructions from the human operators for its operation. On the other hand it provides information about its surroundings for situation assessment. Design and implementation processes of SALVOR are described and its test results are presented in an arena which simulates the calamity zone.
{"title":"Design and implementation of a semi-autonomous mobile search and rescue robot: SALVOR","authors":"A. Denker, M. İşeri","doi":"10.1109/IDAP.2017.8090184","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090184","url":null,"abstract":"Humankind encounters with unprecedented number and scales of disasters which stem from natural and human-made causes. So many victims have suffered severely in those catastrophes that compelled generation and development of search and rescue technology to help victims in future. One of the most important application areas within this scope is the search and rescue robots. The robots equipped with capabilities of sensing and maneuvering in the areas of calamity are enticing more and more attentions from researchers and rescuers. This project aims at realization of a new generation of search and rescue robot which can work in autonomous and semi-autonomous modes and can be used in harsh physical environments of disaster regions to carry out the given tasks more effectively by the use of advanced and economic sensors. In this paper, a mobile search and rescue robot called SALVOR is designed and implemented. SALVOR partly relies on the data from its sensors about the environment and partly on instructions from the human operators for its operation. On the other hand it provides information about its surroundings for situation assessment. Design and implementation processes of SALVOR are described and its test results are presented in an arena which simulates the calamity zone.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127492605","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090246
E. Mengüç, Nurettin Acır
In this paper, a novel adaptive noise canceller (ANC) based on the quaternion valued least mean square algorithm (QLMS) is designed in order to remove electrooculography (EOG) artifacts from electroencephalography (EEG) recordings. The measurement real-valued EOG and EEG signals (FP1, FP2, AF3 and AF4) are first modeled as four-dimensional processes in the quaternion domain. The EOG artifacts are then removed from the EEG signals in the quaternion domain by using the ANC based on QLMS algorithm. The quaternion representation of these signals allows us to remove EOG artifacts from all channels at the same time instead of removing the EOG artifacts in each EEG recordings separately. The simulation results support the proposed approach.
{"title":"An adaptive noise canceller based on QLMS algorithm for removing EOG artifacts in EEG recordings","authors":"E. Mengüç, Nurettin Acır","doi":"10.1109/IDAP.2017.8090246","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090246","url":null,"abstract":"In this paper, a novel adaptive noise canceller (ANC) based on the quaternion valued least mean square algorithm (QLMS) is designed in order to remove electrooculography (EOG) artifacts from electroencephalography (EEG) recordings. The measurement real-valued EOG and EEG signals (FP1, FP2, AF3 and AF4) are first modeled as four-dimensional processes in the quaternion domain. The EOG artifacts are then removed from the EEG signals in the quaternion domain by using the ANC based on QLMS algorithm. The quaternion representation of these signals allows us to remove EOG artifacts from all channels at the same time instead of removing the EOG artifacts in each EEG recordings separately. The simulation results support the proposed approach.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125075735","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090257
Mustafa Kaytan, Ibrahim Berkan Aydilek
It is observed that the number of applications in different areas by using Machine Learning (ML) methods are increased. A variety of tools are also used for these applications. The used tools are developed using various methods. Various software libraries, programming languages and algorithms are used for development of the tools. The used tools can be a variety of different features. So it is difficult to choose a tool for doing application. In this study, some of the current ML tools were investigated. A total of 14 ML tools were investigated in order to facilitate the selection within available tools. General characteristics of the examined tools are described. Similar and different characteristics of the tools have been seen. It is aimed to make choices within the some existing ML tools for to help researchers.
{"title":"A review on machine learning tools","authors":"Mustafa Kaytan, Ibrahim Berkan Aydilek","doi":"10.1109/IDAP.2017.8090257","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090257","url":null,"abstract":"It is observed that the number of applications in different areas by using Machine Learning (ML) methods are increased. A variety of tools are also used for these applications. The used tools are developed using various methods. Various software libraries, programming languages and algorithms are used for development of the tools. The used tools can be a variety of different features. So it is difficult to choose a tool for doing application. In this study, some of the current ML tools were investigated. A total of 14 ML tools were investigated in order to facilitate the selection within available tools. General characteristics of the examined tools are described. Similar and different characteristics of the tools have been seen. It is aimed to make choices within the some existing ML tools for to help researchers.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125213732","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090327
D. Arslan, Merve Erkınay Özdemir, Mustafa Turan Arslan
Pancreatic cancer is the fourth most common cause of cancer-related deaths across the globe and it is one of the most difficult cancer types to recognize early. Early diagnosis of pancreatic cancer is crucial to increase survival for patients. In this study, it was tried to be estimated that persons were pancreatic cancer or healthy using microarray gene expression profile. In accordance with this purpose, Anova method was used to reduce the size of high-dimensional pancreatic cancer gene expression profile and eliminate redundant features. Reduced-size pancreas cancer gene expression profiles were classified by k-nearest neighbor (k-NN) and artificial neural network (ANN) algorithms. The classification accuracy is %82.7 and 84.6% with k-NN, ANN respectively. The promising results indicate that pancreatic cancer can be diagnosed with high accuracy.
{"title":"Diagnosis of pancreatic cancer by pattern recognition methods using gene expression profiles","authors":"D. Arslan, Merve Erkınay Özdemir, Mustafa Turan Arslan","doi":"10.1109/IDAP.2017.8090327","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090327","url":null,"abstract":"Pancreatic cancer is the fourth most common cause of cancer-related deaths across the globe and it is one of the most difficult cancer types to recognize early. Early diagnosis of pancreatic cancer is crucial to increase survival for patients. In this study, it was tried to be estimated that persons were pancreatic cancer or healthy using microarray gene expression profile. In accordance with this purpose, Anova method was used to reduce the size of high-dimensional pancreatic cancer gene expression profile and eliminate redundant features. Reduced-size pancreas cancer gene expression profiles were classified by k-nearest neighbor (k-NN) and artificial neural network (ANN) algorithms. The classification accuracy is %82.7 and 84.6% with k-NN, ANN respectively. The promising results indicate that pancreatic cancer can be diagnosed with high accuracy.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115130163","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090293
Hafzullah Is, A. Müngen, T. Tuncer, Mehmet Kaya
During last 10 years, internet usage network has spread at an unforeseen rate. Concurrently, many services including official transactions have been granted from the internet. By the way, it has become an area where internet users have access to apps and interact with each other over social media. People's internet usage habits have become a domain that can give information about the areas of the population and their interests. In social networks, group analysis and connection predictions are popular terms that construct base of a lot of scientific works. This terms, especially, used for; ads customize, habits and tendency retain or determination of friendship based on same character. Network users can be grouped according to their activity and character, or they can be grouped according to their movement over the network by their estimation algorithms. In this study, all dataset filtered to get anonymous traffic logs that generated by a part of internet users who are in the network of an institution and the community was explored. All logs analyzed according to Category-based diversity, time periods of accesses and usage periods. As expected, communities were established from the habits of users with “Pattern Based Frequency Analysis Method”. Voluntary experimental users whose mac addresses were already defined and belong to determined groups redistributed with specified method. Lastly, via calculating the achievement of correct distribution results the success of method found out.
{"title":"Frequent pattern mining for community dedection in web logs group based habit dedection in community using network traces","authors":"Hafzullah Is, A. Müngen, T. Tuncer, Mehmet Kaya","doi":"10.1109/IDAP.2017.8090293","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090293","url":null,"abstract":"During last 10 years, internet usage network has spread at an unforeseen rate. Concurrently, many services including official transactions have been granted from the internet. By the way, it has become an area where internet users have access to apps and interact with each other over social media. People's internet usage habits have become a domain that can give information about the areas of the population and their interests. In social networks, group analysis and connection predictions are popular terms that construct base of a lot of scientific works. This terms, especially, used for; ads customize, habits and tendency retain or determination of friendship based on same character. Network users can be grouped according to their activity and character, or they can be grouped according to their movement over the network by their estimation algorithms. In this study, all dataset filtered to get anonymous traffic logs that generated by a part of internet users who are in the network of an institution and the community was explored. All logs analyzed according to Category-based diversity, time periods of accesses and usage periods. As expected, communities were established from the habits of users with “Pattern Based Frequency Analysis Method”. Voluntary experimental users whose mac addresses were already defined and belong to determined groups redistributed with specified method. Lastly, via calculating the achievement of correct distribution results the success of method found out.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129709297","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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