Titlebook: Enterprise Information Systems; 16th International C José Cordeiro,Slimane Hammoudi,Joaquim Filipe Conference proceedings 2015 Springer Int

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書目名稱Enterprise Information Systems影響因子(影響力)




書目名稱Enterprise Information Systems影響因子(影響力)學(xué)科排名




書目名稱Enterprise Information Systems網(wǎng)絡(luò)公開度




書目名稱Enterprise Information Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Enterprise Information Systems被引頻次




書目名稱Enterprise Information Systems被引頻次學(xué)科排名




書目名稱Enterprise Information Systems年度引用




書目名稱Enterprise Information Systems年度引用學(xué)科排名




書目名稱Enterprise Information Systems讀者反饋




書目名稱Enterprise Information Systems讀者反饋學(xué)科排名

Dysarthria

Data Fraud Detection: A First General Perspectivehappened at anytime of human mankind, all around the world, and affects all kind of human activities. For instance, betrayers are entities of the society, industry, banks, services, health-care, non-profit organizations, art, science, media or even a government or the Vatican. We consider four main

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Fibroid

Using Complex Correspondences for Integrating Relational Data Sourcesdata. Integrating data raises several challenges, since the designer usually encounters incompatible data models characterized by differences in structure and semantics. One of the hardest challenges is to define correspondences between schema elements (e.g., attributes) to determine how they relate

專橫

Towards an Efficient and Distributed DBSCAN Algorithm Using MapReducehan to those in other groups. Among several types of clustering, density-based clustering algorithms are more efficient in detecting clusters with varied density and different shapes. One of the most important density-based clustering algorithms is DBSCAN. Due to the huge size of generated data by t

神經(jīng)

Discovering Frequent Patterns on Agrometeorological Data with TrieMotifo climate change impacts. In this context, the development of new technologies for monitoring are crucial. Finding previously unknown patterns that frequently occur on time series, known as motifs, is a core task to mine the collected data. In this work we present a method that allows a fast and acc

神經(jīng)

An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Modelsdata-mining researchers in recent years. Traditional approaches only try to forecast the overall fix time of a case when it is reported, without updating this preliminary estimate as long as the case evolves. Clearly, the actions performed on a case can help refine the prediction of its (remaining)

integral

Palliation

Using Data Mining for Prediction of Hospital Length of Stay: An Application of the CRISP-DM Methodol hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Por

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