scholarly journals A New Data Mining and Visualization Tool for Brazilian Educational Indicators

2021 ◽  
Author(s):  
Rodrigo Silveira de Pinho ◽  
Danilo Borges da Silva ◽  
Suzana Matos França de Oliveira
Keyword(s):  
Data Mining ◽  
Open Data ◽  
Easy Access ◽  
Visualization Tool ◽  
Simple Manner ◽  
Educational Indicators ◽  
Educational Studies

The National Institute of Educational Studies and Research Anísio Teixeira provides open data that help to understand Brazilian Education through Educational Indicators. Despite the easy access to the data, it is hard to manipulate and analyze it to understand the educational scenario in different contexts. This work presents a new visualization tool, inspired by the data mining process, which aims to allow the extraction of knowledge through these indicators using selections provided by users in a very simple manner. To show the tool's potential, graphics of several works were recreated and new graphics are presented.

Development of a flow-based planning support system based on open data for the City of Atlanta

2017 ◽  
Vol 46 (2) ◽  
pp. 207-224
Author(s):  
Ge Zhang ◽  
Wenwen Zhang ◽  
Subhrajit Guhathakurta ◽  
Nisha Botchwey
Keyword(s):  
Support System ◽  
Open Data ◽  
Community Planning ◽  
Relevant Information ◽  
Easy Access ◽  
Data Movement ◽  
Planning Support ◽  
Planning Support System ◽  
Analytical Tools ◽  
The City

Open data have come of age with many cities, states, and other jurisdictions joining the open data movement by offering relevant information about their communities for free and easy access to the public. Despite the growing volume of open data, their use has been limited in planning scholarship and practice. The bottleneck is often the format in which the data are available and the organization of such data, which may be difficult to incorporate in existing analytical tools. The overall goal of this research is to develop an open data-based community planning support system that can collect related open data, analyze the data for specific objectives, and visualize the results to improve usability. To accomplish this goal, this study undertakes three research tasks. First, it describes the current state of open data analysis efforts in the community planning field. Second, it examines the challenges analysts experience when using open data in planning analysis. Third, it develops a new flow-based planning support system for examining neighborhood quality of life and health for the City of Atlanta as a prototype, which addresses many of these open data challenges.

scholarly journals Applying Logistic Regression Data mining techniques for Ethiopian Government Agricultural Open Data Sets

2021 ◽  
Vol 10 (2) ◽  
pp. 473-488
Keyword(s):  
Data Mining ◽  
Logistic Regression ◽  
Agricultural Sector ◽  
Model Building ◽  
Open Data ◽  
Research Process ◽  
Attribute Selection ◽  
Sufficient Evidence ◽  
Vegetable Crops ◽  
Logistic Regression Algorithm

Ethiopia has a great agricultural potential because of its vast areas of fertile land, diverse climate, generally adequate rainfall, and large labor force. With its verified importance to the Ethiopian economy, there is sufficient evidence to show that the potential of the agricultural sector can be expanded considerably by attracting investors towards the sector. This study aims at applying classification techniques in developing a predictive model that can estimate yield production of vegetable crops and the correlation of crops based on their class. In the process of building a model, different steps were undertaken. Among the steps, data collection, data preprocessing and model building and validation were the major ones. Different tasks performed in each step are mentioned as follows. The data were collected Food and Agriculture Organization of the United Nations (FAO). Under preprocessing, data cleaning, discretization and attribute selection were done. The final step was model building and validation and it was performed using the selected tools and techniques. The data mining tool used in this research was Weka. In this software the logistic regression algorithm was selected since it is capable to score more accuracy. After successive experiments were done using this software, a model that can classify crop yield as high, medium and low with better accuracy to the extent of 88.6%. Experimental results show that logistic regression is a very helpful tool to depict the contribution of yield estimation and crop correlation. The reported findings are optimistic, making the proposed model a useful tool in the decision making process. Eventually, the whole research process can be a good input for further indepth research

scholarly journals ENSURF: multi-model sea level forecast – implementation and validation results for the IBIROOS and Western Mediterranean regions

Ocean Science ◽  
2012 ◽  
Vol 8 (2) ◽  
pp. 211-226 ◽  
Author(s):  
B. Pérez ◽  
R. Brouwer ◽  
J. Beckers ◽  
D. Paradis ◽  
C. Balseiro ◽  
...  
Keyword(s):  
Real Time ◽  
Sea Level ◽  
Bayesian Model ◽  
Weighted Average ◽  
Western Mediterranean ◽  
Bayesian Model Average ◽  
Easy Access ◽  
Visualization Tool ◽  
Average Technique ◽  
Model Average

Abstract. ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast that makes use of several storm surge or circulation models and near-real time tide gauge data in the region, with the following main goals: 1. providing easy access to existing forecasts, as well as to its performance and model validation, by means of an adequate visualization tool; 2. generation of better forecasts of sea level, including confidence intervals, by means of the Bayesian Model Average technique (BMA). The Bayesian Model Average technique generates an overall forecast probability density function (PDF) by making a weighted average of the individual forecasts PDF's; the weights represent the Bayesian likelihood that a model will give the correct forecast and are continuously updated based on the performance of the models during a recent training period. This implies the technique needs the availability of sea level data from tide gauges in near-real time. The system was implemented for the European Atlantic facade (IBIROOS region) and Western Mediterranean coast based on the MATROOS visualization tool developed by Deltares. Results of validation of the different models and BMA implementation for the main harbours are presented for these regions where this kind of activity is performed for the first time. The system is currently operational at Puertos del Estado and has proved to be useful in the detection of calibration problems in some of the circulation models, in the identification of the systematic differences between baroclinic and barotropic models for sea level forecasts and to demonstrate the feasibility of providing an overall probabilistic forecast, based on the BMA method.

scholarly journals Prediksi Kemenangan eSport DOTA 2 Berdasarkan Data Pertandingan

AVITEC ◽  
2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Eduardus Hardika Sandy Atmaja
Keyword(s):  
Data Mining ◽  
Naive Bayes ◽  
Open Data ◽  
Prediction Method ◽  
Naïve Bayes ◽  
Professional Communities ◽  
Accurate Analysis ◽  
Great Demand ◽  
Analysis System ◽  
General Society

DOTA 2 is one of the eSports that are in great demand both by the general society and the game professional communities. They compete with each other to develop the best strategy to defeat all enemies they faced. In order to develop the best strategy, a good and accurate analysis system is needed. Data mining can be used to solve these problems by digging valuable information from dataset using certain method. Prediction method is one of the methods in data mining that is most appropriate for finding the winning predictions for the DOTA 2 game. One method that is quite simple and can be used is Naive Bayes. The results of this study indicate that Naive Bayes can make predictions well with an accuracy of 98,804 %. The data used in this research as much as 50000 that obtained from open data. It is expected that this research can assist players in providing information for developing game strategies.

scholarly journals Data Management at the French National Audiovisual Institute (Ina)

Atlanti ◽  
2016 ◽  
Vol 26 (1) ◽  
pp. 101-108
Author(s):  
Eleonore Alquier
Keyword(s):  
Data Mining ◽  
Big Data ◽  
General Public ◽  
Open Data ◽  
Digital Technologies ◽  
Data Access ◽  
Technical Data ◽  
Production Processes ◽  
Data Policy ◽  
Online Access

The French National Audiovisual Institute has been responsible since 1974 for the preservation of the audiovisual heritage produced by national broadcasting corporation (or “Office de radio et television française”: ORTF, for French radio and television corporation). The massive digitalization of these collections in the 1990s, the native digital capture of 120 channels since 2001, the opening of a “general public” website in 2006, are some of the steps taken by the Institute to progressively take into account the digital technologies to benefit the audiovisual preservation. This proposal of presentation would provide an update on the evolution of our processing, concerning most specifically a multi-year project which aims, linked to a new big data policy, to harmonize descriptive metadata according to common thesaurus and to streamline production processes as well as to promote new uses of these contents within the Institute (partial automation of documentary processing by automatic detecting of quoted or represented entities (faces, names, …), automatic articulation of documentary and legal metadata, …), but also outside of the Institute (online access to open data, access to media by technical data mining, …).

scholarly journals PRODUCT BUNDLING APPLICATION TO SUPPORT IMPLEMENTATION OF ASSOCIATION RULE MINING USING FP-GROWTH

2021 ◽  
Vol 14 (1) ◽  
pp. 60-63
Author(s):  
Iin Ernawati ◽  
Nurhafifah Matondang
Keyword(s):  
Data Mining ◽  
Electronic Commerce ◽  
Association Rule ◽  
Mobile Application ◽  
Association Rule Mining ◽  
Easy Access ◽  
Online Media ◽  
Rule Mining ◽  
Product Bundling ◽  
Transaction Pattern

Online media has been proven to gave good impact especially in the business field, for opening and widen access to people and society, and so giving more opportunity to any business broader and easy access through electronic commerce (e-commerce). This is the basic idea for the need to improve business reach for a decorative plants store in Tangerang Area. The association transaction pattern as the outcome of data mining process by implementing the Fp-Growth Algorithm that is injected to a mobile application with the purpose to get the buyer’s shopping pattern, which is also packed as the products bundling promotion media and finally open the opportunity to broaden reach for business and information.  

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