Rialto: A Knowledge Discovery suite for data analysis |
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| Affiliation: | 1. ICAR-CNR, Via Bucci 41c, 87036 Rende (CS), Italy;2. Dip. di Matematica e Informatica, Universitá della Calabria, Via Bucci 30b, 87036 Rende (CS), Italy;3. Exeura S.r.l., Via P.A. Cabrai, 87036 Rende (CS), Italy;1. Collins College of Business, The University of Tulsa, 800 South Tucker Drive, Helmerich Hall 118B, Tulsa, OK, 74104, United States;2. Department of Engineering Management and Systems Engineering, Laboratory for Investment and Financial Engineering, Intelligent Systems Center, Missouri University of Science and Technology, 221 Engineering Management, 600 W. 14th Street, Rolla, MO, 65409-0370, United States;3. SphereXX.com, 9142 S. Sheridan, Tulsa, OK, 74133, United States;4. Microsoft Corporation, 205 108th Ave NE #400, Bellevue, WA, 98004, United States;1. Computer Science Department, Instituto Nacional de Astrofísica Óptica y Electrónica (INAOE), Luis Enrique Erro # 1, Puebla 72840, México;2. Faculty of Psychology, Benemérita Universidad Autónoma de Puebla (BUAP), 3 Oriente # 403, Puebla 72000, México;1. Department of Mathematics, College of Natural Sciences, Arba Minch University, Arba Minch, Ethiopia;2. Department of Mathematics, Annamalai University, Annamalainagar - 608002, Tamilnadu, India;1. Information Engineering Department, Universitá Politecnica delle Marche, via Brecce Bianche, 60131 Ancona, Italy;2. Faculty of Mathematics and Computer Science, Eindhoven University of Technology, NL-5600 MB, Eindhoven, The Netherlands |
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| Abstract: | A Knowledge Discovery (KD) process is a complex inter-disciplinary task, where different types of techniques coexist and cooperate for the purpose of extracting useful knowledge from large amounts of data. So, it is desirable having a unifying environment, built on a formal basis, where to design and perform the overall process. In this paper we propose a general framework which formalizes a KD process as an algebraic expression, that is, as a composition of operators representing elementary operations on two worlds: the data and the model worlds. Then, we describe a KD platform, named Rialto, based on such a framework. In particular, we provide the design principles of the underlying architecture, highlight the basic features, and provide a number of experimental results aimed at assessing the effectiveness of the design choices. |
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