We would like to introduce BEECON, an information and event extraction system for business intelligence. this is the first ontology-based system for business documents analysis that is able to detect 41 different type...
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Operators are challenged by the new cloud services, which can modify current traffic pattern. this talk presents the Telefonica I+D view on the evolution towards a transport network ready to support cloud services. It...
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Operators are challenged by the new cloud services, which can modify current traffic pattern. this talk presents the Telefonica I+D view on the evolution towards a transport network ready to support cloud services. It explains the reasons why current transport networks are not efficiently design for a cloud environment and it describes the architecture for a cloud-ready network. To show the feasibility of such cloud-ready network, experimental validations are presented to show the concepts of a cloud-ready transport network.
Logistic regression is well known to the data mining research community as a tool for modeling and classification. the presence of outliers is an unavoidable phenomenon in data analysis. Detection of outliers is impor...
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ISBN:
(纸本)9781467351645
Logistic regression is well known to the data mining research community as a tool for modeling and classification. the presence of outliers is an unavoidable phenomenon in data analysis. Detection of outliers is important to increase the accuracy of the required estimates and for reliable knowledge discovery from the underlying databases. Most of the existing outlier detection methods in regression analysis are based on the single case deletion approach that is inefficient in the presence of multiple outliers because of the well known masking and swamping effects. To avoid these effects the multiple case deletion approach has been introduced. We propose a group deletion approach based diagnostic measure for identifying multiple influential observations in logistic regression. At the same time we introduce a plotting technique that can classify data into outliers, high leverage points, as well as influential and regular observations. this paper has two objectives. First, it investigates the problems of outlier detection in logistic regression, proposes a new method that can find multiple influential observations, and classifies the types of outlier. Secondly, it shows the necessity for proper identification of outliers and influential observations as a prelude for reliable knowledge discovery from modeling and classification via logistic regression. We demonstrate the efficiency of our method, compare the performance withthe existing popular diagnostic methods, and explore the necessity of outlier detection for reliability and robustness in modeling and classification by using real datasets.
Very often, the recognition of a pattern is accompanied by a cognitive process of interpretation and understanding. In the arts and sciences, as well as in our daily lives, we learned patterns from nature and create n...
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In this paper we propose a new model of a Modular Neural Network (MNN) with fuzzy integration based on granular computing. the topology and parameters of the model are optimized with a Hierarchical Genetic Algorithm (...
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ISBN:
(纸本)9783642253294;9783642253300
In this paper we propose a new model of a Modular Neural Network (MNN) with fuzzy integration based on granular computing. the topology and parameters of the model are optimized with a Hierarchical Genetic Algorithm (HGA). the model was applied to the case of human recognition to illustrate its applicability. the proposed method is able to divide the data automatically into sub modules, to work with a percentage of images and select which images will be used for training. We considered, to test this method, the problem of human recognition based on ear, and we used a database with 77 persons (with 4 images each person for this task).
this paper presents a new modular neural network architecture that is used to build a system for patternrecognition based on the iris biometric measurement of persons. In this system, the properties of the person iri...
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ISBN:
(纸本)9783642253294;9783642253300
this paper presents a new modular neural network architecture that is used to build a system for patternrecognition based on the iris biometric measurement of persons. In this system, the properties of the person iris database are enhanced with image processing methods, and the coordinates of the center and radius of the iris are obtained to make a cut of the area of interest by removing the noise around the iris. the inputs to the modular neural network are the processed iris images and the output is the number of the identified person. the integration of the modules was done with a type-2 fuzzy integrator at the level of the sub modules, and with a gating network at the level of the modules.
In this paper, we propose a new framework of providing Handwritten Character recognition as a Service (HCRaaS) via Internet, based on cloud computing technology. Using the proposed Cloud-based recognition platform, we...
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ISBN:
(纸本)9780769545202
In this paper, we propose a new framework of providing Handwritten Character recognition as a Service (HCRaaS) via Internet, based on cloud computing technology. Using the proposed Cloud-based recognition platform, we would be able to apply many advanced algorithms in practice, such as modified quadratic discriminant function (MQDF) and SVM classifier used for large scale character recognition, writing adaptation technology, and handwriting Chinese word/textline recognitionthat usually involve large storage and computation cost. Withthe merits and characteristics of HCRaaS, users of different mobile devices are not only no longer subject to local computing capacity and storage resource constraints, but also, they can benefit from higher recognition accuracy and personalized service with low hardware costs. the experimental results show that, the proposed HCRaaS system based on Cloud computing can provide reliable handwriting solution across different mobile OS with higher recognition performance.
the proceedings contain 84 papers. the topics discussed include: new measure of boolean factor analysis quality;mechanisms of adaptive spatial integration in a neural model of cortical motion processing;self-organized...
ISBN:
(纸本)9783642202810
the proceedings contain 84 papers. the topics discussed include: new measure of boolean factor analysis quality;mechanisms of adaptive spatial integration in a neural model of cortical motion processing;self-organized short-term memory mechanism in spiking neural network;approximation of functions by multivariable hermite basis: a hybrid method;using patternrecognition to predict driver intent;neural networks committee for improvement of metal's mechanical properties estimates;logarithmic multiplier in hardware implementation of neural networks;a robust learning model for dealing with missing values in many-core architectures;a model of saliency-based selective attention for machine vision inspection application;grapheme-phoneme translator for Brazilian Portuguese;and improvement of inventory control under parametric uncertainty and constraints.
Actually associative memories have demonstrated to be useful in pattern processing field. Hopfield model is an autoassociative memory that has problems in the recalling phase;one of them is the time of convergence or ...
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ISBN:
(纸本)9783642253294;9783642253300
Actually associative memories have demonstrated to be useful in pattern processing field. Hopfield model is an autoassociative memory that has problems in the recalling phase;one of them is the time of convergence or non convergence in certain cases withpatterns bad recovered. In this paper, a new algorithm for the Hopfield associative memory eliminates iteration processes reducing time computing and uncertainty on pattern recalling. this algorithm is implemented using a corrective vector which is computed using the Hopfield memory. the corrective vector adjusts misclassifications in output recalled patterns. Results show a good performance of the proposed algorithm, providing an alternative tool for the patternrecognition field.
the proceedings contain 84 papers. the topics discussed include: new measure of boolean factor analysis quality;mechanisms of adaptive spatial integration in a neural model of cortical motion processing;self-organized...
ISBN:
(纸本)9783642202667
the proceedings contain 84 papers. the topics discussed include: new measure of boolean factor analysis quality;mechanisms of adaptive spatial integration in a neural model of cortical motion processing;self-organized short-term memory mechanism in spiking neural network;approximation of functions by multivariable hermite basis: a hybrid method;using patternrecognition to predict driver intent;neural networks committee for improvement of metal's mechanical properties estimates;logarithmic multiplier in hardware implementation of neural networks;a robust learning model for dealing with missing values in many-core architectures;a model of saliency-based selective attention for machine vision inspection application;grapheme-phoneme translator for Brazilian Portuguese;and improvement of inventory control under parametric uncertainty and constraints.
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