Pub Date : 2017-11-01DOI: 10.1109/ISKE.2017.8258811
Fei Teng, Rong Tang, Tianrui Li
Online social networks are now recognized as an important platform for propagating information. Recently, a lot of efforts are made to predict the popularity of social information, to help the government and companies effectively control and guide public opinions. Information propagation in social networks exist many different temporal patterns, which are useful reference for predicting the future spreading of news. Considering temporal patterns are related to the network structure and information content, some researchers formulated a time series clustering problem to obtain temporal patterns in social networks. Previous clustering based algorithms take each cluster center as a typical propagation pattern, and then classify prediction object into its nearest-neighbor cluster. However, the nearest pattern can not fit the prediction object very precisely. This paper proposes a novel E-CTPM (Ego-Clustering based Temporal Prediction Model). E-CTPM utilizes the prediction object itself as a fixed cluster center, which can attract the most similar time series into one cluster and generate an ego-pattern for the prediction object. The tailored pattern fits the prediction object well, so it is suitable to indicate the future propagation. Experiments are carried on twitter and phrase datasets, with the results that E-CTPM outperforms the existing algorithms by achieving lower prediction bias and prediction variance. Meanwhile, E-CTPM has general applicability, which is able to work with multiple clustering methods and avoids the prediction difference resulting from classification methods.
{"title":"Ego-clustering based propagation prediction of time series in social networks","authors":"Fei Teng, Rong Tang, Tianrui Li","doi":"10.1109/ISKE.2017.8258811","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258811","url":null,"abstract":"Online social networks are now recognized as an important platform for propagating information. Recently, a lot of efforts are made to predict the popularity of social information, to help the government and companies effectively control and guide public opinions. Information propagation in social networks exist many different temporal patterns, which are useful reference for predicting the future spreading of news. Considering temporal patterns are related to the network structure and information content, some researchers formulated a time series clustering problem to obtain temporal patterns in social networks. Previous clustering based algorithms take each cluster center as a typical propagation pattern, and then classify prediction object into its nearest-neighbor cluster. However, the nearest pattern can not fit the prediction object very precisely. This paper proposes a novel E-CTPM (Ego-Clustering based Temporal Prediction Model). E-CTPM utilizes the prediction object itself as a fixed cluster center, which can attract the most similar time series into one cluster and generate an ego-pattern for the prediction object. The tailored pattern fits the prediction object well, so it is suitable to indicate the future propagation. Experiments are carried on twitter and phrase datasets, with the results that E-CTPM outperforms the existing algorithms by achieving lower prediction bias and prediction variance. Meanwhile, E-CTPM has general applicability, which is able to work with multiple clustering methods and avoids the prediction difference resulting from classification methods.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133269972","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258795
Caijuan Zhang, Ming Jiang
In the criminal law of all countries, the crime of willful and malicious injury is a common accusation. The offender must bear the criminal responsibility and be punished by criminal penalty. However, because of the complexity of the circumstances for adjudication, the various kinds of statutory sentence, and the wide extent of the fixed-term imprisonment, the sentencing imbalance can be caused, such as different responsibility for same crime and different punishments for same responsibilities. In this paper, the penalty for the crime of willful and malicious injury is the main object of study, and some rules of sentencing reasoning are put forward to restrict the discretion of judges and to improve the impartiality and enforce-ability of punishment.
{"title":"An explanation of the sentencing of willful and malicious injury crime based on inference rules","authors":"Caijuan Zhang, Ming Jiang","doi":"10.1109/ISKE.2017.8258795","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258795","url":null,"abstract":"In the criminal law of all countries, the crime of willful and malicious injury is a common accusation. The offender must bear the criminal responsibility and be punished by criminal penalty. However, because of the complexity of the circumstances for adjudication, the various kinds of statutory sentence, and the wide extent of the fixed-term imprisonment, the sentencing imbalance can be caused, such as different responsibility for same crime and different punishments for same responsibilities. In this paper, the penalty for the crime of willful and malicious injury is the main object of study, and some rules of sentencing reasoning are put forward to restrict the discretion of judges and to improve the impartiality and enforce-ability of punishment.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133939343","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258736
Xiaoyong Lin, Jie Ma, Zeqiu Zhang, Chao Chen, Yun Xia, Yang Yu, Tingting Qiu, Xiaoming Wang
User centric network (UCN) brought a new concept of all routers to be intelligent and definable, intelligent wireless terminals implement more video online service than general webpage exploring service, in the time of content is the king, how to provide a best user experience for the video content user under intelligent wireless routers(IWR) is a key focus in the current research of user centric network. This paper proposed a scheme of intelligent pipe between Policy server and IWR, and designed a novel content popularity compensation (CPC) algorithm in user centric network framework, the IWR obtained the user attributes and video content popularity, used the parameter of content popularity compensation index (CPI) to integrate the classified user weight (CUW) and content popularity level (CPL), the modified satisfaction degree (MSD) was designed to replace of the general index of user satisfaction degree, such as linear satisfaction degree (LSD) and simple logarithmic satisfaction (SLS). The scheduling rule was to get a maximized system MSD, and the measurement of user average satisfaction (UAS) was the evaluation standard of CPC. The simulations results showed that the CPC got the better performance than that of routine algorithms, such as max-min fairness (MMF) and Utility function (ULF), the CPC algorithm could push on the intelligent wireless router in smart home and bring a novel video content quality of experience (QoE) of future wireless video online users.
{"title":"CPC: A novel content popularity compensation algorithm for intelligent wireless router in user centric network","authors":"Xiaoyong Lin, Jie Ma, Zeqiu Zhang, Chao Chen, Yun Xia, Yang Yu, Tingting Qiu, Xiaoming Wang","doi":"10.1109/ISKE.2017.8258736","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258736","url":null,"abstract":"User centric network (UCN) brought a new concept of all routers to be intelligent and definable, intelligent wireless terminals implement more video online service than general webpage exploring service, in the time of content is the king, how to provide a best user experience for the video content user under intelligent wireless routers(IWR) is a key focus in the current research of user centric network. This paper proposed a scheme of intelligent pipe between Policy server and IWR, and designed a novel content popularity compensation (CPC) algorithm in user centric network framework, the IWR obtained the user attributes and video content popularity, used the parameter of content popularity compensation index (CPI) to integrate the classified user weight (CUW) and content popularity level (CPL), the modified satisfaction degree (MSD) was designed to replace of the general index of user satisfaction degree, such as linear satisfaction degree (LSD) and simple logarithmic satisfaction (SLS). The scheduling rule was to get a maximized system MSD, and the measurement of user average satisfaction (UAS) was the evaluation standard of CPC. The simulations results showed that the CPC got the better performance than that of routine algorithms, such as max-min fairness (MMF) and Utility function (ULF), the CPC algorithm could push on the intelligent wireless router in smart home and bring a novel video content quality of experience (QoE) of future wireless video online users.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122839476","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258737
Yin-feng Liang
Aiming at the problem of low precision of keyword extraction in traditional complex network method, we propose a keyword extraction method based on an improved weighted complex network, called IWCN algorithm. First, based on the word semantic similarity, we construct a complex network to obtain semantic weight of words. Next, the statistical weight of words is obtained by the introduction of term frequency (TF) and inverse document frequency (IDF). Finally, we combine semantic and statistical weights of words to get keywords. Comparing to traditional complex network approach, the proposed method can avoid the deviations and thus improves extraction accuracy. Simulation results shows that the proposed method achieves higher precision and recall.
{"title":"Chinese keyword extraction based on weighted complex network","authors":"Yin-feng Liang","doi":"10.1109/ISKE.2017.8258737","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258737","url":null,"abstract":"Aiming at the problem of low precision of keyword extraction in traditional complex network method, we propose a keyword extraction method based on an improved weighted complex network, called IWCN algorithm. First, based on the word semantic similarity, we construct a complex network to obtain semantic weight of words. Next, the statistical weight of words is obtained by the introduction of term frequency (TF) and inverse document frequency (IDF). Finally, we combine semantic and statistical weights of words to get keywords. Comparing to traditional complex network approach, the proposed method can avoid the deviations and thus improves extraction accuracy. Simulation results shows that the proposed method achieves higher precision and recall.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"262 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122928958","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258735
Wei Wei, Chonghui Guo, Jingfeng Chen, Zhen Zhang
The government work report of the State Council is a kind of comprehensive policy text. This paper uses text mining technology to carry out a comprehensive multi-granularity, multi-level quantitative analysis of the government work reports, which has a great practical and instructive significance for relevant personnels to understand the evolution of domain knowledge in a short time. Firstly, a series of text preprocessing is done by using the Chinese word segmentation tool combined with three kind of dictionary built by authors, i.e., the domain word dictionary, the domain synonym dictionary and the domain stopword dictionary. Then, according to the co-occurrence information of words in the government work reports, we attempt to conduct topic modeling on the corpus consisted of all the government work reports and single government work report respectively, Finally, we find 12 latent topics for the corpus, such as the "Economic reform", "Agriculture", "Government construction", "Defense military" and so on. Based on the 12 topics, we conduct the topic modeling on every single government work report, with which topic evolution analysis is carried out over the whole period of all government work reports.
{"title":"Textual topic evolution analysis based on term co-occurrence: A case study on the government work report of the State Council (1954–2017)","authors":"Wei Wei, Chonghui Guo, Jingfeng Chen, Zhen Zhang","doi":"10.1109/ISKE.2017.8258735","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258735","url":null,"abstract":"The government work report of the State Council is a kind of comprehensive policy text. This paper uses text mining technology to carry out a comprehensive multi-granularity, multi-level quantitative analysis of the government work reports, which has a great practical and instructive significance for relevant personnels to understand the evolution of domain knowledge in a short time. Firstly, a series of text preprocessing is done by using the Chinese word segmentation tool combined with three kind of dictionary built by authors, i.e., the domain word dictionary, the domain synonym dictionary and the domain stopword dictionary. Then, according to the co-occurrence information of words in the government work reports, we attempt to conduct topic modeling on the corpus consisted of all the government work reports and single government work report respectively, Finally, we find 12 latent topics for the corpus, such as the \"Economic reform\", \"Agriculture\", \"Government construction\", \"Defense military\" and so on. Based on the 12 topics, we conduct the topic modeling on every single government work report, with which topic evolution analysis is carried out over the whole period of all government work reports.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128946290","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258727
Junxuan He, Hailiang Zhao, Yi Jiang
Based on evaluation vectors derived from single factor and the comprehensive evaluation results of some known typical objects, the sample data is classfied into different kinds, and the weight vector of the multi-factor comprehensive evaluation problem is transformed into the solution of an overdetermined systems, which consist of inconsistent linear equation constituted by the vectors of single factor evaluation and the comprehensive evaluation results. The approximate numerical relationship of the standard sample data from the typical objects is fitted with the least squares method, so that the weight vectors to different kinds of objects for comprehensive evaluation are obtained. A learning and correction way to find a multiple linear weighted synthesis model with minimum number of sub-model for the classification of object is presented. A typical object is employed as the center for every sub-model. In applications, the objects are assigned to that class whose center is closest to the objects firstly, and the evaluation result can be derived by the corresponding sub-model. Finally, the effectiveness of the proposed method is illustrated by an example.
{"title":"Method for determining comprehensive weight vector based on multiple linear fitting","authors":"Junxuan He, Hailiang Zhao, Yi Jiang","doi":"10.1109/ISKE.2017.8258727","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258727","url":null,"abstract":"Based on evaluation vectors derived from single factor and the comprehensive evaluation results of some known typical objects, the sample data is classfied into different kinds, and the weight vector of the multi-factor comprehensive evaluation problem is transformed into the solution of an overdetermined systems, which consist of inconsistent linear equation constituted by the vectors of single factor evaluation and the comprehensive evaluation results. The approximate numerical relationship of the standard sample data from the typical objects is fitted with the least squares method, so that the weight vectors to different kinds of objects for comprehensive evaluation are obtained. A learning and correction way to find a multiple linear weighted synthesis model with minimum number of sub-model for the classification of object is presented. A typical object is employed as the center for every sub-model. In applications, the objects are assigned to that class whose center is closest to the objects firstly, and the evaluation result can be derived by the corresponding sub-model. Finally, the effectiveness of the proposed method is illustrated by an example.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116990128","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258748
Thanaphon Phukseng, S. Sodsee
This research presents a trust assigning method for recommendation systems by considering a user similarity and social trust. Herein, the proposed method consists of three main processes, namely trust calculation, neighbor filtering, and items rating prediction. To evaluate, the FilmTrust dataset was used to verify its prediction performance. The results shown that the significant measures, such as the mean absolute error (MAE) and percentage of accuracy, they were around 0.197 and 80% with a trust walk in a social network, λ = 5, respectively.
{"title":"Calculating trust by considering user similarity and social trust for recommendation systems","authors":"Thanaphon Phukseng, S. Sodsee","doi":"10.1109/ISKE.2017.8258748","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258748","url":null,"abstract":"This research presents a trust assigning method for recommendation systems by considering a user similarity and social trust. Herein, the proposed method consists of three main processes, namely trust calculation, neighbor filtering, and items rating prediction. To evaluate, the FilmTrust dataset was used to verify its prediction performance. The results shown that the significant measures, such as the mean absolute error (MAE) and percentage of accuracy, they were around 0.197 and 80% with a trust walk in a social network, λ = 5, respectively.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116745470","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258743
Abhishek M. Appaji, H. N. Suma, M. Madhurya, S. Sonia, A. Vinekar
Retinopathy of Prematurity (ROP) is a disease of the eye affecting the prematurely — born babies. It results in unorganized growth of retinal blood vessels which may result in scarring and retinal detachment. The severity of the disease is measured[1] by the stage of the disease and the presence or absence of Plus disease leading to Aggressive Posterior Retinopathy of Prematurity-APROP. The tortuosity index which is indicative of the twisting of the blood vessel calculated. This facilitates in deciding if the new born has APROP or not. A higher value of the index suggests that the baby has developed Plus disease, leading to APROP. The major disadvantage lies in the fact that the number of specialists in Retinopathy are comparatively less. [2] Thus many times this disease goes unnoticed and the baby might be blinded for life. Main objective is to curb the distance between the specialists and the patients in remote area. The importance lies in the fact that the doctor is able to receive the results and can prioritize appointments as per requirements and patients in remote areas can channelize their travel to meet the doctor.
{"title":"Comprehensive analysis of retinopathy of prematurity based on tortuosity with development of web connectivity","authors":"Abhishek M. Appaji, H. N. Suma, M. Madhurya, S. Sonia, A. Vinekar","doi":"10.1109/ISKE.2017.8258743","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258743","url":null,"abstract":"Retinopathy of Prematurity (ROP) is a disease of the eye affecting the prematurely — born babies. It results in unorganized growth of retinal blood vessels which may result in scarring and retinal detachment. The severity of the disease is measured[1] by the stage of the disease and the presence or absence of Plus disease leading to Aggressive Posterior Retinopathy of Prematurity-APROP. The tortuosity index which is indicative of the twisting of the blood vessel calculated. This facilitates in deciding if the new born has APROP or not. A higher value of the index suggests that the baby has developed Plus disease, leading to APROP. The major disadvantage lies in the fact that the number of specialists in Retinopathy are comparatively less. [2] Thus many times this disease goes unnoticed and the baby might be blinded for life. Main objective is to curb the distance between the specialists and the patients in remote area. The importance lies in the fact that the doctor is able to receive the results and can prioritize appointments as per requirements and patients in remote areas can channelize their travel to meet the doctor.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127150301","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258723
M. Xu, Yifan Chu
To address the issue of risk detection in e-commerce platform, this paper presents an intelligent risk detection method that can detect risk quickly and accurately without hampering the performance of the system. This method makes full use of all kinds of data collected in on-line transactions and extracts the features from them. Some theorems such as Bayes network and clustering are also introduced to classify the featured data and finally work out a solution for risk detection.
{"title":"A intelligent risk detection method in online transactions","authors":"M. Xu, Yifan Chu","doi":"10.1109/ISKE.2017.8258723","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258723","url":null,"abstract":"To address the issue of risk detection in e-commerce platform, this paper presents an intelligent risk detection method that can detect risk quickly and accurately without hampering the performance of the system. This method makes full use of all kinds of data collected in on-line transactions and extracts the features from them. Some theorems such as Bayes network and clustering are also introduced to classify the featured data and finally work out a solution for risk detection.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127226985","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 : 2017-11-01DOI: 10.1109/ISKE.2017.8258731
Fengxia Zhang
Distributivity equations has been widely studied involving different classes of aggregation functions from t-norms and t-conorms to various aggregation operators, such as uninorms, t-operators and their generalizations. In this paper, we follow on these works by investigating Mayor's aggregation operators and semi-uninorms.
{"title":"On distributivity equations for Mayor's aggregation operators and semi-uninorms","authors":"Fengxia Zhang","doi":"10.1109/ISKE.2017.8258731","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258731","url":null,"abstract":"Distributivity equations has been widely studied involving different classes of aggregation functions from t-norms and t-conorms to various aggregation operators, such as uninorms, t-operators and their generalizations. In this paper, we follow on these works by investigating Mayor's aggregation operators and semi-uninorms.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126227269","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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