Results 251 to 260 of about 161,462 (303)

Mining fuzzy association rules in databases

ACM SIGMOD Record, 1998
Data mining is the discovery of previously unknown, potentially useful and hidden knowledge in databases. In this paper, we concentrate on the discovery of association rules. Many algorithms have been proposed to find association rules in databases with binary attributes. We introduce the fuzzy association rules of the form, 'If
Chan Man Kuok, Ada Fu, Man Hon Wong
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Text Mining using Fuzzy Association Rules

2004
In this paper, fuzzy association rules are used in a text framework. Text transactions are defined based on the concept of fuzzy association rules considering each attribute as a term of a collection. The purpose of the use of text mining technologies presented in this paper is to assist users to find relevant information.
M. J. Martín-Bautista, D. Sánchez, J. M. Serrano, M. A. Vila   +3 more
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Mining Association Rules from Fuzzy DataCubes

2010
The use of online analytical processing (OLAP) systems as data sources for data mining techniques has been widely studied and has resulted in what is known as online analytical mining (OLAM). As a result of both the use of OLAP technology in new fields of knowledge and the merging of data from different sources, it has become necessary for models to ...
Nicolás Marín, Carlos Molina, Daniel Sánchez, M. Amparo Vila   +3 more
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Mining Fuzzy Association Rules: An Overview

2006
The main aim of this paper is to present a revision of the most relevant results about the use of Fuzzy Sets in Data Mining, specifically in relation with the discovery of Association Rules. Fuzzy Sets Theory has been shown to be a very useful tool in Data Mining in order to represent the so-called Association Rules in a natural and human ...
M. Delgado, N. Manín, M. J. Martín-Bautista, D. Sánchez, M. -A. Vila   +4 more
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A Novel Three-Way Deep Learning Approach for Multigranularity Fuzzy Association Analysis of Time Series Data

IEEE transactions on fuzzy systems
Discovering valuable knowledge from massive time series data is challenging due to sophisticated temporal relationships and inherent uncertainties. This article proposes a new multigranularity fuzzy association analysis of multigranularity incorporated ...
Chunmao Jiang, Ying Duan
semanticscholar   +1 more source

Early warning of enterprise finance risk of big data mining in internet of things based on fuzzy association rules

Neural computing & applications (Print), 2020
Hongyun Shang, Duan Lu, Qingyuan Zhou
semanticscholar   +1 more source

Mining Quantitative and Fuzzy Association Rules

2005
The problem of mining association rules from databases was introduced by Agrawal, Imielinski, & Swami (1993). In this problem, we give a set of items and a large collection of transactions, which are subsets (baskets) of these items. The task is to find relationships between the occurrences of various items within those baskets.
Hong Shen, Susumu Horiguchi
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Contextual generic association rules visualization using hierarchical fuzzy meta-rules

2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542), 2005
Traditional framework for mining association rules has pointed out the derivation of many redundant rules, in order to be reliable in a decision making process, such discovered rules have to be concise and easily understandable for users or as well as an input to visualization tools. We present a 3D histograms-based visualization prototype for handling
S.B. Yahia, E.M. Nguifo
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Clustering Association Rules with Fuzzy Concepts

2009
Association rules constitute a widely accepted technique to identify frequent patterns inside huge volumes of data. Practitioners prefer the straightforward interpretability of rules, however, depending on the nature of the underlying data the number of induced rules can be intractable large. Even reasonably sized result sets may contain a large amount
Matthias Steinbrecher, Rudolf Kruse
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Mining fuzzy spatial association rules

2001
ÖZ BELÎRSÎZ COĞRAFÎ İLÎŞKÎ KURALLARI MADENCİLİĞİ Kaçar, Esen Yüksek Lisans, Bilgisayar Mühendisliği Bölümü Tez Yöneticisi: Doç. Dr. Nihan Kesim Çiçekli Temmuz 2001, 70 sayfa Coğrafi bilgi sistemlerinde, varolan mekansal verileri anlamak ve kullanmak için, ilgi çekici, saklı bilgileri ve genel ilişkileri ortaya çıkarmak çok önemlidir. Bu saklı bilgileri
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