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Sanchez-Hernandez G.,GREC ESADE URL | Sanchez-Hernandez G.,Polytechnic University of Catalonia | Agell N.,GREC ESADE URL | Aguado J.C.,Polytechnic University of Catalonia
Frontiers in Artificial Intelligence and Applications | Year: 2013

In this paper the design of a natural language generation (NLG) system is introduced to qualitatively describe the most important characteristics of each class, cluster or segment previously defined by means of a classification or clustering process. An adaptation of a generic architecture for data-to-text systems consisting of four stages is proposed. It includes the detection of the most relevant patterns of the data and the definition of a grammar that generates the natural language description of the considered clusters. A case study addressing a challenge in a marketing environment is included. The study takes place in a business-to-business (B2B) environment, in which a firm distributes its products via other firms. © 2013 The authors and IOS Press. All rights reserved.


Sanchez G.,GREC ESADE URL | Sanchez G.,Polytechnic University of Catalonia | Sama A.,Polytechnic University of Catalonia | Ruiz F.J.,Polytechnic University of Catalonia | Agell N.,GREC ESADE URL
Frontiers in Artificial Intelligence and Applications | Year: 2010

In this paper a new forecasting methodology to be used on time series prediction is introduced. The considered nonlinear method is based on support vector machines (SVM) using an interval kernel. An extended intersection kernel is introduced to discriminate between disjoint intervals in reference to the existing distance among them. The model presented is applied to forecast exchange ratios using six world's major currencies. The results obtained show that SVMs based on interval kernel have a similar behavior than other SVM classical forecasting approaches, allowing its performance to be seen as very promising when using high frequency data. © 2010 The authors and IOS Press. All rights reserved.

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