A novel exemplar-based image inpainting algorithm is proposed for solving the deficiencies of the classical Criminisi method, such as the error repair accumulation, high time complexity caused by the unreasonable design of the patch priority, inaccuracy criterion and its global search strategy. Thus, we construct a local structure measurement function by introducing the structure tensor theory, and optimize the means of patch priority. On that basis, we design a matching criterion. Experiments show that the improved algorithm has greater advantages on the fidelity of image structure compared with the Criminisi method. Besides, the improved algorithm makes progresses in both subjective visual effect and objective indexes, such as peak signal-to-noise ratio (PSNR), repair error and the running time compared with some of the typical image restoration algorithms proposed recent years.
{"title":"A Novel Exemplar-Based Image Inpainting Algorithm","authors":"Y. Liu, Chanjuan Liu, Hailin Zou, Shusen Zhou, Qian Shen, Tongtong Chen","doi":"10.1109/INCoS.2015.15","DOIUrl":"https://doi.org/10.1109/INCoS.2015.15","url":null,"abstract":"A novel exemplar-based image inpainting algorithm is proposed for solving the deficiencies of the classical Criminisi method, such as the error repair accumulation, high time complexity caused by the unreasonable design of the patch priority, inaccuracy criterion and its global search strategy. Thus, we construct a local structure measurement function by introducing the structure tensor theory, and optimize the means of patch priority. On that basis, we design a matching criterion. Experiments show that the improved algorithm has greater advantages on the fidelity of image structure compared with the Criminisi method. Besides, the improved algorithm makes progresses in both subjective visual effect and objective indexes, such as peak signal-to-noise ratio (PSNR), repair error and the running time compared with some of the typical image restoration algorithms proposed recent years.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124518770","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}
Alejandro Baldominos Gómez, P. I. Viñuela, Y. Sáez, B. Manderick
Medical literature have recognized physical activity as a key factor for a healthy life due to its remarkable benefits. However, there is a great variety of physical activities and not all of them have the same effects on health nor require the same effort. As a result, and due to the ubiquity of commodity devices able to track users' motion, there is an increasing interest on performing activity recognition in order to detect the type of activity carried out by the subjects and being able to credit them for their effort, which has been detected as a key requirement to promote physical activity. This paper proposes a novel approach for performing activity recognition using Monte Carlo Schemata Search (MCSS) for feature selection and random forests for classification. To validate this approach we have carried out an evaluation over PAMAP2, a public dataset on physical activity available in UCI Machine Learning repository, enabling replication and assessment. The experiments are conducted using leave-one-subject-out cross validation and attain classification accuracies of over 93% by using roughly one third of the total set of features. Results are promising, as they outperform those obtained in other works on the same dataset and significantly reduce the set of features used, which could translate in a decrease of the number of sensors required to perform activity recognition and, as a result, a reduction of costs.
{"title":"Monte Carlo Schemata Searching for Physical Activity Recognition","authors":"Alejandro Baldominos Gómez, P. I. Viñuela, Y. Sáez, B. Manderick","doi":"10.1109/INCoS.2015.24","DOIUrl":"https://doi.org/10.1109/INCoS.2015.24","url":null,"abstract":"Medical literature have recognized physical activity as a key factor for a healthy life due to its remarkable benefits. However, there is a great variety of physical activities and not all of them have the same effects on health nor require the same effort. As a result, and due to the ubiquity of commodity devices able to track users' motion, there is an increasing interest on performing activity recognition in order to detect the type of activity carried out by the subjects and being able to credit them for their effort, which has been detected as a key requirement to promote physical activity. This paper proposes a novel approach for performing activity recognition using Monte Carlo Schemata Search (MCSS) for feature selection and random forests for classification. To validate this approach we have carried out an evaluation over PAMAP2, a public dataset on physical activity available in UCI Machine Learning repository, enabling replication and assessment. The experiments are conducted using leave-one-subject-out cross validation and attain classification accuracies of over 93% by using roughly one third of the total set of features. Results are promising, as they outperform those obtained in other works on the same dataset and significantly reduce the set of features used, which could translate in a decrease of the number of sensors required to perform activity recognition and, as a result, a reduction of costs.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126110410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The routing information is hard to maintain and the energy is limited in highly dynamic wireless sensor network. To solve these problems, energy-saving geographic routing (ESGR) is proposed, which does not maintain the network topology and can save energy. A node broadcast its position information to its neighboring nodes before transmitting data. The neighboring nodes compute the position of the virtual relay node using the data transmitter position, the base station position and the energy consumption for circuits and propagation. The neighboring nodes determine whether to become the relay node through competition based on its position, the destination position and the virtual relay node position. The simulation shows that the proposed algorithm is better than BLR, because of the lower energy consumption and lower packet loss ratio. The ESGR algorithm is more appropriate for highly dynamic wireless network.
{"title":"An Energy-saving Geographic Routing in Wireless Sensor Network","authors":"Xiao-ou Song","doi":"10.1109/INCoS.2015.27","DOIUrl":"https://doi.org/10.1109/INCoS.2015.27","url":null,"abstract":"The routing information is hard to maintain and the energy is limited in highly dynamic wireless sensor network. To solve these problems, energy-saving geographic routing (ESGR) is proposed, which does not maintain the network topology and can save energy. A node broadcast its position information to its neighboring nodes before transmitting data. The neighboring nodes compute the position of the virtual relay node using the data transmitter position, the base station position and the energy consumption for circuits and propagation. The neighboring nodes determine whether to become the relay node through competition based on its position, the destination position and the virtual relay node position. The simulation shows that the proposed algorithm is better than BLR, because of the lower energy consumption and lower packet loss ratio. The ESGR algorithm is more appropriate for highly dynamic wireless network.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115897649","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}
A campus-based Social Networking System (SNS) has been newly designed and implemented to realize network-based smart community like domain-oriented SNS for collaborative design and decision making in a relatively short period. It can play a role to provide information sharing and communicating. Students of the design education course of our college always need to learn both of knowledge and techniques, the former is necessary to design some objects and the latter are essential to utilize tools as well as equipments. It is important to provide not only knowledge but also techniques in efficient and effective ways. For the sake of building large-scale poster for college promotion and the publicity of entrance examination, we must build up such a poster by means of the above information sharing and communicating system. This paper reports our SNS-based collaboration scheme and its application to both of collaborative design education and our real task of poster design. The scheme can play a role of such a design bed and communicating environment of collaborative design and decision making.With our SNS-based collaboration scheme, we can perform the real collaborative design for design education and poster creation in a short period. Its performance let the collaborative design and decision making more fruitful.
{"title":"Application of SNS-Based Collaboration Scheme into Reproductive Design Education and Collaborative Design with Information Sharing","authors":"Masatoshi Imai, Y. Imai","doi":"10.1109/INCoS.2015.93","DOIUrl":"https://doi.org/10.1109/INCoS.2015.93","url":null,"abstract":"A campus-based Social Networking System (SNS) has been newly designed and implemented to realize network-based smart community like domain-oriented SNS for collaborative design and decision making in a relatively short period. It can play a role to provide information sharing and communicating. Students of the design education course of our college always need to learn both of knowledge and techniques, the former is necessary to design some objects and the latter are essential to utilize tools as well as equipments. It is important to provide not only knowledge but also techniques in efficient and effective ways. For the sake of building large-scale poster for college promotion and the publicity of entrance examination, we must build up such a poster by means of the above information sharing and communicating system. This paper reports our SNS-based collaboration scheme and its application to both of collaborative design education and our real task of poster design. The scheme can play a role of such a design bed and communicating environment of collaborative design and decision making.With our SNS-based collaboration scheme, we can perform the real collaborative design for design education and poster creation in a short period. Its performance let the collaborative design and decision making more fruitful.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127563488","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}
Tetsuya Oda, Makoto Ikeda, L. Barolli, F. Xhafa, M. Takizawa
Wireless Mesh Networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In our previous work, we evaluated WMN-GA system which is based on Genetic Algorithms (GAs) to find an optimal location assignment for mesh routers. In this paper, we evaluate the performance of two WMN architectures considering throughput, delay, jitter and fairness index metrics. For simulations, we used ns-3 and Optimized Link State Routing (OLSR). We compare the performance for Distributed Coordination Function (DCF) and Enhanced Distributed Channel Access (EDCA) for normal distribution of mesh clients by sending multiple Constant Bit Rate (CBR) flows in the network. The simulation results show that the throughput of I/B WMN is higher than Hybrid WMN architecture. The delay and jitter of Hybrid WMN is a lower compared with I/B WMN. The fairness index of 10 and 20 flows is higher than 30 flows for both architectures. In I/B architecture the fairness index of DCF is higher than EDCA. However, for Hybrid WMN, the fairness index of EDCA is higher than DCF.
{"title":"A GA-Based Simulation System for WMNs: Performance Analysis of WMN-GA System for Different WMN Architectures Considering DCF and EDCA","authors":"Tetsuya Oda, Makoto Ikeda, L. Barolli, F. Xhafa, M. Takizawa","doi":"10.1109/INCoS.2015.81","DOIUrl":"https://doi.org/10.1109/INCoS.2015.81","url":null,"abstract":"Wireless Mesh Networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In our previous work, we evaluated WMN-GA system which is based on Genetic Algorithms (GAs) to find an optimal location assignment for mesh routers. In this paper, we evaluate the performance of two WMN architectures considering throughput, delay, jitter and fairness index metrics. For simulations, we used ns-3 and Optimized Link State Routing (OLSR). We compare the performance for Distributed Coordination Function (DCF) and Enhanced Distributed Channel Access (EDCA) for normal distribution of mesh clients by sending multiple Constant Bit Rate (CBR) flows in the network. The simulation results show that the throughput of I/B WMN is higher than Hybrid WMN architecture. The delay and jitter of Hybrid WMN is a lower compared with I/B WMN. The fairness index of 10 and 20 flows is higher than 30 flows for both architectures. In I/B architecture the fairness index of DCF is higher than EDCA. However, for Hybrid WMN, the fairness index of EDCA is higher than DCF.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130875989","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}
In this paper, we discuss the evaluation of the probabilistic extraction as introduced in [1], by considering three different datasets introduced in [1] - [3]. the results show the potential of the approach, as well as its reliability and efficiency when analyzing datasets with different properties and structures. This is part of ongoing research aiming to provide a tool to extract, assess and visualize intelligence extracted from large unstructured datasets.
{"title":"A Comprehensive Evaluation of a Novel Approach to Probabilistic Information Extraction from Large Unstructured Datasets","authors":"M. Trovati","doi":"10.1109/INCoS.2015.36","DOIUrl":"https://doi.org/10.1109/INCoS.2015.36","url":null,"abstract":"In this paper, we discuss the evaluation of the probabilistic extraction as introduced in [1], by considering three different datasets introduced in [1] - [3]. the results show the potential of the approach, as well as its reliability and efficiency when analyzing datasets with different properties and structures. This is part of ongoing research aiming to provide a tool to extract, assess and visualize intelligence extracted from large unstructured datasets.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115727041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The closeness centrality can be considered as the natural distance metric between pairs of nodes in connected graphs. This paper is the initial study of the influence of the closeness centrality of the graph built on the basis of the differential evolution dynamics to the differential evolution convergence rate. Our algorithm is based on the principle that the differential evolution creates graph for each generation, where nodes represent the individuals and edges the relationships between them. For each individual the closeness centrality is computed and on the basis of its value the individuals are selected in the mutation step of the algorithm. The higher value of the closeness centrality means the higher probability to become the parent in the mutation step. This enhancement has been incorporated in the classical differential evolution and a set of 21 well-known benchmark functions has been used to test and evaluate the performance of the proposed enhancement of the differential evolution. The experimental results and statistical analysis indicate that the enhanced algorithm performs better or at least comparable to its original version.
{"title":"Differential Evolution Enhanced by the Closeness Centrality: Initial Study","authors":"Lenka Skanderová, Tomáš Fabián, I. Zelinka","doi":"10.1109/INCoS.2015.65","DOIUrl":"https://doi.org/10.1109/INCoS.2015.65","url":null,"abstract":"The closeness centrality can be considered as the natural distance metric between pairs of nodes in connected graphs. This paper is the initial study of the influence of the closeness centrality of the graph built on the basis of the differential evolution dynamics to the differential evolution convergence rate. Our algorithm is based on the principle that the differential evolution creates graph for each generation, where nodes represent the individuals and edges the relationships between them. For each individual the closeness centrality is computed and on the basis of its value the individuals are selected in the mutation step of the algorithm. The higher value of the closeness centrality means the higher probability to become the parent in the mutation step. This enhancement has been incorporated in the classical differential evolution and a set of 21 well-known benchmark functions has been used to test and evaluate the performance of the proposed enhancement of the differential evolution. The experimental results and statistical analysis indicate that the enhanced algorithm performs better or at least comparable to its original version.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114911894","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}
Linguistic word nets usually focus on the semantic content and content relations of nouns while not taking into account to what degree those nouns can also reflect visual impressions in a user specific manner. Recently Color Design SNS like COLOURlovers or Adobe Color CC have gained popularity and the huge corpus of available data allows for gaining new insights into the way user associate color designs with impression words. We present the results of an experimental study for finding Kansei aspects of impression words and related user models by physiological closeness of color designs. The closeness relation between color designs is based on intensity impression matching, where a suitable way of reflecting intensity impression of contrasting colors was selected based on subjective impressions evaluation experiments. The first results of this novel combination of physiology and subjective impression can give raise to further investigations into such a direction.
语言词网通常关注名词的语义内容和内容关系，而不考虑这些名词在多大程度上也能以用户特定的方式反映视觉印象。最近，像COLOURlovers或Adobe Color CC这样的色彩设计社交网站越来越受欢迎，大量的可用数据可以让我们对用户将色彩设计与印象词联系起来的方式获得新的见解。我们提出了一项通过色彩设计的生理亲近度来寻找印象词的感性方面和相关用户模型的实验研究结果。色彩设计之间的密切关系是基于强度印象匹配，即通过主观印象评价实验选择一种合适的方式来反映对比色的强度印象。这种生理学和主观印象的新结合的第一个结果可以引起对这一方向的进一步研究。
{"title":"Towards a Kansei WordNet by Color Design SNS Evaluation","authors":"Kaori Yoshida, Dwilya Makiwan, M. Köppen","doi":"10.1109/INCoS.2015.57","DOIUrl":"https://doi.org/10.1109/INCoS.2015.57","url":null,"abstract":"Linguistic word nets usually focus on the semantic content and content relations of nouns while not taking into account to what degree those nouns can also reflect visual impressions in a user specific manner. Recently Color Design SNS like COLOURlovers or Adobe Color CC have gained popularity and the huge corpus of available data allows for gaining new insights into the way user associate color designs with impression words. We present the results of an experimental study for finding Kansei aspects of impression words and related user models by physiological closeness of color designs. The closeness relation between color designs is based on intensity impression matching, where a suitable way of reflecting intensity impression of contrasting colors was selected based on subjective impressions evaluation experiments. The first results of this novel combination of physiology and subjective impression can give raise to further investigations into such a direction.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115068955","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}
With the advent of the era of big data, the data scale being processed is more and more large, which brings new challenge to the design of privacy-preserving protocols. For the Private Set Intersection (PSI) problem, when the sizes of sets is large, keeping its efficiency and scalability is becoming very difficult. In addition, elements in these sets are likely to be twodimensional data, which usually contains an attribute and its corresponding weight. That increases the difficulty to solve the problem. Some creative protocols were proposed to settle the PSI problem recently. However, these protocols can only protect the privacy of the one-dimension elements of users' private sets. And when the elements are two-dimensional, they are not work. In this paper, we propose an efficient and scalable protocol for sets which have two-dimensional elements. Thorough security analysis indicate that our scheme is effective and efficient.
{"title":"Two-Dimensional Private Set Intersection in Big Data","authors":"Xiuguang Li, Pan Feng, Shuguang Liu","doi":"10.1109/INCoS.2015.77","DOIUrl":"https://doi.org/10.1109/INCoS.2015.77","url":null,"abstract":"With the advent of the era of big data, the data scale being processed is more and more large, which brings new challenge to the design of privacy-preserving protocols. For the Private Set Intersection (PSI) problem, when the sizes of sets is large, keeping its efficiency and scalability is becoming very difficult. In addition, elements in these sets are likely to be twodimensional data, which usually contains an attribute and its corresponding weight. That increases the difficulty to solve the problem. Some creative protocols were proposed to settle the PSI problem recently. However, these protocols can only protect the privacy of the one-dimension elements of users' private sets. And when the elements are two-dimensional, they are not work. In this paper, we propose an efficient and scalable protocol for sets which have two-dimensional elements. Thorough security analysis indicate that our scheme is effective and efficient.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115095176","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}
Undesirable emails (spam) are increasingly becoming a big problem nowadays, not only for users, but also for Internet service providers. Therefore, the design of new algorithms detecting the spam is currently one of the research hot-topics. We define two requirements and use them simultaneously. The first requirement is a low rate of falsely detected emails which has an impact on the algorithm performance. The second requirement is a fast detection of spams. It minimizes the delay in receiving emails. In this paper, we focus our effort on the first requirement. To solve this problem we applied network community analysis. The approach is to find communities - groups of same emails. In this paper, we present a new nearest community classifier and apply it in the field of spam detection. The obtained results are very close to Bayesian Spam Filter. We achieved 93.78% accuracy. The algorithm can detect 80.72% of spam emails and 98.01% non-spam emails.
{"title":"Spam Detection Based on Nearest Community Classifier","authors":"Michal Prilepok, M. Kudelka","doi":"10.1109/INCoS.2015.75","DOIUrl":"https://doi.org/10.1109/INCoS.2015.75","url":null,"abstract":"Undesirable emails (spam) are increasingly becoming a big problem nowadays, not only for users, but also for Internet service providers. Therefore, the design of new algorithms detecting the spam is currently one of the research hot-topics. We define two requirements and use them simultaneously. The first requirement is a low rate of falsely detected emails which has an impact on the algorithm performance. The second requirement is a fast detection of spams. It minimizes the delay in receiving emails. In this paper, we focus our effort on the first requirement. To solve this problem we applied network community analysis. The approach is to find communities - groups of same emails. In this paper, we present a new nearest community classifier and apply it in the field of spam detection. The obtained results are very close to Bayesian Spam Filter. We achieved 93.78% accuracy. The algorithm can detect 80.72% of spam emails and 98.01% non-spam emails.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116789478","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：