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Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2019; 20th International C Hujun Yin,David Camacho,Richard Allmendinger Confere

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A Hybrid Model for Fraud Detection on Purchase Orders,wever, due to the massive volume of the data available today, it is becoming impossible to manually check all the transactions of a company, hence only a small sample of the data is verified. This work presents a new approach through the usage of signature detection with clustering techniques to inc
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Users Intention Based on Twitter Features Using Text Analytics,g calculation. The posts features are divided into three sets: tweets textual features, users features, and network contextual features. In this paper, our focus is on tweets analysing textual features. As a result of this paper, we were able to create intentions profiles for 2960 users based on tex
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A Hybrid Approach to Time Series Classification with Shapelets,for time series classification. The two most prominent shapelet based classification algorithms are the shapelet transform (ST) and learned shapelets (LS). One significant difference between these approaches is that ST is data driven, whereas LS searches the entire shapelet space through stochastic
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An Ensemble Algorithm Based on Deep Learning for Tuberculosis Classification, has been allowed for the greater availability of data, which has not been foreign in the field of medicine. This data can be used to train supervised Machine Learning algorithms. Taking into account that this data can be in form of images, several ML algorithms, such as Artificial Neural Networks,
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,A Data-Driven Approach to Automatic Extraction of Professional Figure Profiles from Résumés,ware applications aimed at helping professional recruiters in the process, only recently with Industry 4.0 there has been a real interest in implementing autonomous and data-driven approaches that can provide insights and practical assistance to recruiters..In this paper, we propose a framework that
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Retrieving and Processing Information from Clinical Algorithm via Formal Concept Analysis,al data sets are being actively introduced into clinical practice, which, in turn, generates the new arrays of data. The natural solution here is the clinical information systems (CIS) which help the physicians in clinical decision making as well as in training and research. In this paper we propose
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