Symbolic Data Analysis: A Paradigm for Complex Data Mining?
نویسندگان
چکیده
ACM Digital Library; Bacon’s Media Directory; Cabell’s Directories; DBLP; Google Scholar; INSPEC; JournalTOCs; MediaFinder; ProQuest Biological Science Journals; ProQuest Illustrata: Natural Science; ProQuest Natural Sciences Journals; ProQuest SciTech Journals; The Standard Periodical Directory; Ulrich’s Periodicals Directory Copyright The International Journal of Signs and Semiotic Systems (IJSSS) (ISSN 2155-5028; eISSN 2155-5036), Copyright © 2014 IGI Global. All rights, including translation into other languages reserved by the publisher. No part of this journal may be reproduced or used in any form or by any means without witten permission from the publisher, except for noncommercial, educational use including classroom teaching purposes. Product or company names used in this journal are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. The views expressed in this journal are those of the authors but not neccessarily of IGI Global. Research Articles
منابع مشابه
A New Algorithm for Optimization of Fuzzy Decision Tree in Data Mining
Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. The most comprehensible decision trees have been designed for perfect symbolic data. Classical crisp decision trees (DT) are widely applied to classification t...
متن کاملMining association rules with multiple Min-supports - Application to Symbolic data
RÉSUMÉ. Les données symboliques sont un nouveau paradigme de description de données quand les données sont plus complexes que la forme tabulaire. Elles supportent des données plus structurées ayant des variations internes telles que des distributions, des règles telles que des taxonomies. Depuis son introduction [1], le problème d’extraction de règles d'association à partir de grandes bases de ...
متن کاملFar beyond the classical data models: symbolic data analysis
This paper introduces symbolic data analysis, explaining how it extends the classical data models to take into account more complete and complex information. Several examples motivate the approach, before the modeling of variables assuming new types of realizations are formally presented. Some methods for the (multivariate) analysis of symbolic data are presented and discussed. This is however ...
متن کاملBayesian paradigm for analysing count data in longitudina studies using Poisson-generalized log-gamma model
In analyzing longitudinal data with counted responses, normal distribution is usually used for distribution of the random efffects. However, in some applications random effects may not be normally distributed. Misspecification of this distribution may cause reduction of efficiency of estimators. In this paper, a generalized log-gamma distribution is used for the random effects which includes th...
متن کاملArchitecture for Symbolic Object Warehouse
Much information stored in current databases is not always present at necessary different levels of detail or granularity for Decision-Making Processes (DMP). Some organizations have implemented the use of central database Data Warehouse (DW) where information performs analysis tasks. This fact depends on the Information Systems (IS) maturity, the type of informational requirements or necessiti...
متن کاملData Mining for Management and Rehabilitation of Water Systems: The Evolutionary Polynomial Regression Approach
Risk-based management and rehabilitation of water distribution systems requires that company asset data are collected and also that a methodology is available to efficiently extract information from data. The process of extracting useful information from data is called knowledge discovery and at its core is data mining. This automated analysis of large or complex datasets is performed to determ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- IJSSS
دوره 3 شماره
صفحات -
تاریخ انتشار 2014