ºÝºÝߣshows by User: danielgribel / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: danielgribel / Fri, 18 Dec 2015 22:28:44 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: danielgribel Forest Cover type prediction /slideshow/forest-cover-type-prediction-56288946/56288946 forestcover-151218222844
Predicting forest cover type from cartographic variables only (not remotely sensed data).]]>
Predicting forest cover type from cartographic variables only (not remotely sensed data).]]> Fri, 18 Dec 2015 22:28:44 GMT /slideshow/forest-cover-type-prediction-56288946/56288946 danielgribel@slideshare.net(danielgribel) Forest Cover type prediction danielgribel Predicting forest cover type from cartographic variables only (not remotely sensed data). <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/forestcover-151218222844-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Predicting forest cover type from cartographic variables only (not remotely sensed data).
Forest Cover type prediction from Daniel Gribel
]]> 1942 5 https://cdn.slidesharecdn.com/ss_thumbnails/forestcover-151218222844-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A clustering-based approach to detect probable outcomes of lawsuits /slideshow/a-clusteringbased-approach-to-detect-probable-outcomes-of-lawsuits/43069702 tcc-141229090756-conversion-gate01
The large amount of data coming from the numerous lawsuits in progress or already judged by the STF (Brazilian Supreme Court) consists of non-structured data, which leads to a large number of hidden or unknown information, as some relationships between lawsuits that are not explicit in the available data. These conditions also contribute to generate non-intuitive influences between variables and to increase the degree of uncertainty. However, many lawsuits can be decided based in certain patterns like: (i) the comparison to lawsuits with similar features (area of the Law, parties involved, nature of the claim, rapporteur, etc), (ii) the comparison to outcomes taken by a judge with a history of judging similar lawsuits, and (iii) the comparison to laws considered in past cases. All these parameters and some other patterns observed in past lawsuits provide a framework of non-structured data that can be transformed in useful data to predict new outcomes. This work proposes an approach to identify possible judgement outcomes that considers aspects beyond the analytical techniques. Through the use of similarity calculations and clustering mechanisms, the proposed solution was built in order to find the most similar lawsuits for a new instance that is being tested. By analysing some meta-data, it is possible to find a similar case already judged, since the amount of data provided by the judicial system are quite large. By the developing of a program that detects clusters and compiles past votes, the results shown that is possible to verify the most likely outcome and to detect its degree of uncertainty.]]>
The large amount of data coming from the numerous lawsuits in progress or already judged by the STF (Brazilian Supreme Court) consists of non-structured data, which leads to a large number of hidden or unknown information, as some relationships between lawsuits that are not explicit in the available data. These conditions also contribute to generate non-intuitive influences between variables and to increase the degree of uncertainty. However, many lawsuits can be decided based in certain patterns like: (i) the comparison to lawsuits with similar features (area of the Law, parties involved, nature of the claim, rapporteur, etc), (ii) the comparison to outcomes taken by a judge with a history of judging similar lawsuits, and (iii) the comparison to laws considered in past cases. All these parameters and some other patterns observed in past lawsuits provide a framework of non-structured data that can be transformed in useful data to predict new outcomes. This work proposes an approach to identify possible judgement outcomes that considers aspects beyond the analytical techniques. Through the use of similarity calculations and clustering mechanisms, the proposed solution was built in order to find the most similar lawsuits for a new instance that is being tested. By analysing some meta-data, it is possible to find a similar case already judged, since the amount of data provided by the judicial system are quite large. By the developing of a program that detects clusters and compiles past votes, the results shown that is possible to verify the most likely outcome and to detect its degree of uncertainty.]]> Mon, 29 Dec 2014 09:07:56 GMT /slideshow/a-clusteringbased-approach-to-detect-probable-outcomes-of-lawsuits/43069702 danielgribel@slideshare.net(danielgribel) A clustering-based approach to detect probable outcomes of lawsuits danielgribel The large amount of data coming from the numerous lawsuits in progress or already judged by the STF (Brazilian Supreme Court) consists of non-structured data, which leads to a large number of hidden or unknown information, as some relationships between lawsuits that are not explicit in the available data. These conditions also contribute to generate non-intuitive influences between variables and to increase the degree of uncertainty. However, many lawsuits can be decided based in certain patterns like: (i) the comparison to lawsuits with similar features (area of the Law, parties involved, nature of the claim, rapporteur, etc), (ii) the comparison to outcomes taken by a judge with a history of judging similar lawsuits, and (iii) the comparison to laws considered in past cases. All these parameters and some other patterns observed in past lawsuits provide a framework of non-structured data that can be transformed in useful data to predict new outcomes. This work proposes an approach to identify possible judgement outcomes that considers aspects beyond the analytical techniques. Through the use of similarity calculations and clustering mechanisms, the proposed solution was built in order to find the most similar lawsuits for a new instance that is being tested. By analysing some meta-data, it is possible to find a similar case already judged, since the amount of data provided by the judicial system are quite large. By the developing of a program that detects clusters and compiles past votes, the results shown that is possible to verify the most likely outcome and to detect its degree of uncertainty. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/tcc-141229090756-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The large amount of data coming from the numerous lawsuits in progress or already judged by the STF (Brazilian Supreme Court) consists of non-structured data, which leads to a large number of hidden or unknown information, as some relationships between lawsuits that are not explicit in the available data. These conditions also contribute to generate non-intuitive influences between variables and to increase the degree of uncertainty. However, many lawsuits can be decided based in certain patterns like: (i) the comparison to lawsuits with similar features (area of the Law, parties involved, nature of the claim, rapporteur, etc), (ii) the comparison to outcomes taken by a judge with a history of judging similar lawsuits, and (iii) the comparison to laws considered in past cases. All these parameters and some other patterns observed in past lawsuits provide a framework of non-structured data that can be transformed in useful data to predict new outcomes. This work proposes an approach to identify possible judgement outcomes that considers aspects beyond the analytical techniques. Through the use of similarity calculations and clustering mechanisms, the proposed solution was built in order to find the most similar lawsuits for a new instance that is being tested. By analysing some meta-data, it is possible to find a similar case already judged, since the amount of data provided by the judicial system are quite large. By the developing of a program that detects clusters and compiles past votes, the results shown that is possible to verify the most likely outcome and to detect its degree of uncertainty.
A clustering-based approach to detect probable outcomes of lawsuits from Daniel Gribel
]]> 1426 6 https://cdn.slidesharecdn.com/ss_thumbnails/tcc-141229090756-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 QAP: Metodos construtivos, 2-opt, Busca tabu https://pt.slideshare.net/slideshow/qap-bucas-locais-2opt-e-busca-tabu/30264252 qap-presentation-140121113349-phpapp01
Problema quadrático de alocação (QAP): Métodos construtivos, Busca local 2-opt, Busca tabu.]]>
Problema quadrático de alocação (QAP): Métodos construtivos, Busca local 2-opt, Busca tabu.]]> Tue, 21 Jan 2014 11:33:49 GMT https://pt.slideshare.net/slideshow/qap-bucas-locais-2opt-e-busca-tabu/30264252 danielgribel@slideshare.net(danielgribel) QAP: Metodos construtivos, 2-opt, Busca tabu danielgribel Problema quadrático de alocação (QAP): Métodos construtivos, Busca local 2-opt, Busca tabu. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/qap-presentation-140121113349-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Problema quadrático de alocação (QAP): Métodos construtivos, Busca local 2-opt, Busca tabu.
from Daniel Gribel
]]> 1361 17 https://cdn.slidesharecdn.com/ss_thumbnails/qap-presentation-140121113349-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 DicVoice! /slideshow/dicvoice-16494425/16494425 dicvoice-slides-130212163338-phpapp02
DicVoice! is an e-dictionary with audio synthesizer. Provides the pronunciation of words in three languages ​​and has been designed with accessibility tools.]]>
DicVoice! is an e-dictionary with audio synthesizer. Provides the pronunciation of words in three languages ​​and has been designed with accessibility tools.]]> Tue, 12 Feb 2013 16:33:38 GMT /slideshow/dicvoice-16494425/16494425 danielgribel@slideshare.net(danielgribel) DicVoice! danielgribel DicVoice! is an e-dictionary with audio synthesizer. Provides the pronunciation of words in three languages ​​and has been designed with accessibility tools. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dicvoice-slides-130212163338-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> DicVoice! is an e-dictionary with audio synthesizer. Provides the pronunciation of words in three languages ​​and has been designed with accessibility tools.
DicVoice! from Daniel Gribel
]]> 328 3 https://cdn.slidesharecdn.com/ss_thumbnails/dicvoice-slides-130212163338-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-danielgribel-48x48.jpg?cb=1525979550 https://cdn.slidesharecdn.com/ss_thumbnails/forestcover-151218222844-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/forest-cover-type-prediction-56288946/56288946 Forest Cover type pred... https://cdn.slidesharecdn.com/ss_thumbnails/tcc-141229090756-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/a-clusteringbased-approach-to-detect-probable-outcomes-of-lawsuits/43069702 A clustering-based app... https://cdn.slidesharecdn.com/ss_thumbnails/qap-presentation-140121113349-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/qap-bucas-locais-2opt-e-busca-tabu/30264252 QAP: Metodos construti...