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2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)最新文献

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Comparison of similarity measures in context of rules clustering 规则聚类环境下相似性度量的比较
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001163
A. Nowak-Brzezińska, Tomasz Rybotycki
{"title":"Comparison of similarity measures in context of rules clustering","authors":"A. Nowak-Brzezińska, Tomasz Rybotycki","doi":"10.1109/INISTA.2017.8001163","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001163","url":null,"abstract":"This paper introduces five similarity measures, very well known in literature, but not because of using them to compare rules between themselves and choose the most similar one. Rules in knowledge bases are a very specific type of data representation and it is necessary to compare them carefully. The goal of the paper is to analyze the influence of using different similarity measures on the number of clusters, or the size of the representatives of the created clusters of rules. The results of the experiments are presented in Section III in order to discuss the significance of the analyzed measures and methods of rules creating.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130390760","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}
引用次数: 2
Outlier detection in medical data using linguistic summaries 用语言摘要检测医学数据中的异常值
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001191
A. Duraj
{"title":"Outlier detection in medical data using linguistic summaries","authors":"A. Duraj","doi":"10.1109/INISTA.2017.8001191","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001191","url":null,"abstract":"The main purpose of outlier detection algorithms is to find a new feature that is distinct from the other features of the vector in the analyzed data set. This paper concerns outlier detection in medical databases, and the supervised and unsupervised methods used in detection of outliers in medical data are discussed. Moreover, the author's original method for detecting outliers based on linguistic summaries is presented.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128444971","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}
引用次数: 17
Grade Analysis for households segmentation based on energy usage patterns 基于能源使用模式的家庭划分等级分析
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001151
T. Zabkowski, Krzysztof Gajowniczek
{"title":"Grade Analysis for households segmentation based on energy usage patterns","authors":"T. Zabkowski, Krzysztof Gajowniczek","doi":"10.1109/INISTA.2017.8001151","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001151","url":null,"abstract":"The Grade Correspondence Analysis (GCA) with posterior clustering and visualization is introduced and applied to individual households' electricity usage data. The main task of this analysis is to identify a way of representing the variability of a households behavior and to develop an efficient way of clustering the households into a few, usable and homogenous groups. The regularity in terms of the electricity usage is useful information for organizations to allow accurate demand planning with the aim of improving the overall efficiency of the network. The approach is tested using data from 46 households located in Austin, Texas, USA and monitored for 14 months at a sampling interval of 1 hour.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"37 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131933298","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}
引用次数: 1
Performance comparision of different momentum techniques on deep reinforcement learning 不同动量技术在深度强化学习中的性能比较
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001175
Mehmet Sarigul, M. Avci
{"title":"Performance comparision of different momentum techniques on deep reinforcement learning","authors":"Mehmet Sarigul, M. Avci","doi":"10.1109/INISTA.2017.8001175","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001175","url":null,"abstract":"Increase in popularity of deep convolutional neural networks in many different areas leads to increase in the use of these networks in reinforcement learning. Training a huge deep neural network structure by using simple gradient descent learning can take quite a long time. Some additional learning approaches should be utilized to solve this problem. One of these techniques is use of momentum which accelerates gradient descent learning. Although momentum techniques are mostly developed for supervised learning problems, it can also be used for reinforcement learning problems. However, its efficiency may vary due to the dissimilarities in two training learning processes. In this paper, the performances of different momentum techniques are compared for one of the reinforcement learning problems; Othello game benchmark. Test results show that the Nesterov accelerated momentum technique provided a more effective generalization on benchmark","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133037379","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}
引用次数: 3
The stability analysis of Bat Algorithm Bat算法的稳定性分析
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001133
Janusz P. Papliński, Miroslaw Lazoryszczak
{"title":"The stability analysis of Bat Algorithm","authors":"Janusz P. Papliński, Miroslaw Lazoryszczak","doi":"10.1109/INISTA.2017.8001133","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001133","url":null,"abstract":"The equations describing the position and movement of the new individuals in Bath Algorithm have the form of difference equations. The analysis of the behavior of solutions of this equation and in particular its stability is possible, after omitting of randomness in parameters and treatment of the algorithm as stationary. The simplify analysis of the choice of parameters of the bat algorithm based on the linear stability and behavior of the algorithm is presented in the paper. The study indicates the recommended areas of the location of the parameters, and it shows how the different parameters affect the behavior of the algorithm. A simple tool to speed up the tuning of the algorithm was obtained.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128841335","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}
引用次数: 2
Assessing the quality of a Consensus determined using a multi-level approach 评估使用多层次方法确定的共识的质量
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001145
Adrianna Kozierkiewicz-Hetmanska, Marcin Pietranik
{"title":"Assessing the quality of a Consensus determined using a multi-level approach","authors":"Adrianna Kozierkiewicz-Hetmanska, Marcin Pietranik","doi":"10.1109/INISTA.2017.8001145","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001145","url":null,"abstract":"The following paper investigates a multilevel approach to data integration using the widely accepted Consensus Theory. We focus on an issue related to an initial classification of raw input data into groups that can be integrated in parallel. A final consensus is a result of the integration of obtained partial outcomes. Our main research concerns an application of Fleiss' kappa value, which in the literature is a well known measure that describes how consonant the data in a selected set are. In other words - for a given set of values, the higher the value of this measure, the higher its inner consistency. Therefore, we have attempted to answer the question whether or not the initial data should be divided into coherent groups or into highly divergent subsets, that better represent the whole input. We present a theoretical background, broad description of a series of experiments that we have performed and their statistical analysis.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128475539","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}
引用次数: 5
A new approach to zone identification based on considering features with high semantic richness 基于考虑高语义丰富度特征的区域识别新方法
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001201
K. Badie, N. Asadi, M. Mahmoudi
{"title":"A new approach to zone identification based on considering features with high semantic richness","authors":"K. Badie, N. Asadi, M. Mahmoudi","doi":"10.1109/INISTA.2017.8001201","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001201","url":null,"abstract":"In this paper, we propose a new approach to zone identification based on considering features with high semantic richness such as specialized names and mode of verbs belonging to a text's domain of interest and besides that mode of verbs, while taking into account features with less computational cost compared to those of conventional methods. Out of the scenarios of selecting features for identifying a zone based on classifying the sentences in a text, we came to notice that in the scenario where specialized names and mode of verbs are taken into account together with reduced versions of conventional features including history, an accuracy rate of 61% (resp. 81%) is obtained which is higher than those belonging to both Liakata's and Fisas's approach. Also, to have a genuine comparison, both Liakata's and Fisas's corpuses are used in our experiments. Such accuracy is obtained at the place where less computational cost is taken for extracting the features.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125613392","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}
引用次数: 1
Using mutual information for feature selection in programmatic advertising 利用互信息进行程序化广告特征选择
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001173
Michał Ciesielczyk
{"title":"Using mutual information for feature selection in programmatic advertising","authors":"Michał Ciesielczyk","doi":"10.1109/INISTA.2017.8001173","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001173","url":null,"abstract":"Click-through rate estimation, the core task of programmatic display advertising, is associated with typical big data problems. Online algorithms for generalized linear models, such as Logistic Regression, are the most widely used data mining techniques for learning at such a massive scale. Since these models are unable to capture the underlying nonlinear data patterns, conjunction features are often introduced. This paper is focused on the problem of selecting the most informative 2nd and 3rd order conjunction features used in Logistic Regression. The performance of different feature selection methods based on mutual information is compared over a real-world dataset with over 10 million records. The empirical evaluation show the effectiveness of the proposed approach.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126856402","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}
引用次数: 1
Learning ℓ1-penalized logistic regressions with smooth approximation 用光滑逼近学习1惩罚逻辑回归
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001144
J. Klimaszewski, M. Sklyar, M. Korzeń
{"title":"Learning ℓ1-penalized logistic regressions with smooth approximation","authors":"J. Klimaszewski, M. Sklyar, M. Korzeń","doi":"10.1109/INISTA.2017.8001144","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001144","url":null,"abstract":"The paper presents comparison of learning logistic regression model with different penalty terms. Main part of the paper concerns sparse regression, which includes absolute value function. This function is not strictly convex, thus common optimizers cannot be used directly. In the paper we show that in those cases smooth approximation of absolute value function can be effectively used either in the case of lasso regression or in fussed-lasso like case. One of examples focuses on two dimensional analogue of fussed-lasso model. The experimental results present the comparison of our implementations (in C++ and Python) on three benchmark datasets.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133178161","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}
引用次数: 2
Processing occlusions using elastic-net hierarchical MAX model of the visual cortex 使用视觉皮层弹性网分层MAX模型处理闭塞
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-01 DOI: 10.1109/INISTA.2017.8001150
Ali Alameer, P. Degenaar, K. Nazarpour
{"title":"Processing occlusions using elastic-net hierarchical MAX model of the visual cortex","authors":"Ali Alameer, P. Degenaar, K. Nazarpour","doi":"10.1109/INISTA.2017.8001150","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001150","url":null,"abstract":"Humans can recognise objects under partial occlusion. Machine-based approaches cannot reliably recognise objects and scenes in the presence of occlusion. This paper investigates the use of the elastic net hierarchical MAX (En-HMAX) model to handle occlusions. Our experiments show that the En-HMAX model achieves an accuracy of ∼70%, when ∼50% artificial occlusions are applied to the centre of the visual object-field. Furthermore, when the same percentage of occlusion is applied to the peripheral, the model reports higher accuracies. A similar degree of robustness has been observed when recognising scenes. The results suggest that cortex-like models, such as the En-HMAX are reliable for solving the occlusion challenge.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129009765","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}
引用次数: 3
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