Using distributed apriori association rule and classical apriori mining algorithms for grid based knowledge discovery

2010 ◽  
Author(s):  
R. Sumithra ◽  
Sujni Paul
Keyword(s):  
Knowledge Discovery ◽  
Association Rule ◽  
Mining Algorithms ◽  
Grid Based

Discovering Both Positive and Negative Fuzzy Association Rules in Large Transaction Databases

2006 ◽  
Vol 10 (3) ◽  
pp. 287-294 ◽  
Author(s):  
Jianchao Han ◽  
◽  
Mohsen Beheshti
Keyword(s):  
Knowledge Discovery ◽  
Association Rules ◽  
Association Rule ◽  
Positive Association ◽  
Negative Association ◽  
Fuzzy Association Rules ◽  
Novel Approach ◽  
Negative Association Rules ◽  
Fuzzy Association Rule ◽  
Mining Algorithms

Mining association rules is an important task of dara mining and knowledge discovery. Traditional association rules mining is built on transaction databases, which has some limitations. Two of these limitations are 1) each transaction merely contains binary items, meaning that an item either occurs in a transaction or not; 2) only positive association rules are discovered, while negative associations are ignored. Mining fuzzy association rules has been proposed to address the first limitation, while mining algorithms for negative association rules have been developed to resolve the second limitation. In this paper, we combine these two approaches to propose a novel approach for mining both positive and negative fuzzy association rules. The interestingness measure for both positive and negative fuzzy association rule is proposed, the algorithm for mining these rules is described, and an illustrative example is presented to demonstrate how the measure and the algorithm work.

scholarly journals Present State-of-The-Art of Association Rule Mining Algorithms

2019 ◽  
Vol 9 (1) ◽  
pp. 6398-6405
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
State Of The Art ◽  
Synthetic Data ◽  
Data Sets ◽  
Evolutionary Analysis ◽  
Rule Mining ◽  
Transaction Database ◽  
Mining Algorithms

A Data mining is the method of extracting useful information from various repositories such as Relational Database, Transaction database, spatial database, Temporal and Time-series database, Data Warehouses, World Wide Web. Various functionalities of Data mining include Characterization and Discrimination, Classification and prediction, Association Rule Mining, Cluster analysis, Evolutionary analysis. Association Rule mining is one of the most important techniques of Data Mining, that aims at extracting interesting relationships within the data. In this paper we study various Association Rule mining algorithms, also compare them by using synthetic data sets, and we provide the results obtained from the experimental analysis

scholarly journals Finding Efficient Positive and Negative Itemsets Using Interestingness Measures

2018 ◽  
Vol 7 (4.36) ◽  
pp. 533
Author(s):  
P. Asha ◽  
T. Prem Jacob ◽  
A. Pravin
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Data Gathering ◽  
Unstructured Data ◽  
Rule Mining ◽  
Interestingness Measures ◽  
Data Mining Algorithms ◽  
Data Formats ◽  
Mining Algorithms ◽  
Rare Itemsets

Currently, data gathering techniques have increased through which unstructured data creeps in, along with well defined data formats. Mining these data and bringing out useful patterns seems difficult. Various data mining algorithms were put forth for this purpose. The associated patterns generated by the association rule mining algorithms are large in number. Every ARM focuses on positive rule mining and very few literature has focussed on rare_itemsets_mining. The work aims at retrieving the rare itemsets that are of most interest to the user by utilizing various interestingness measures. Both positive and negative itemset mining would be focused in this work.  

Grid-Based Data Mining and Knowledge Discovery

2004 ◽  
pp. 19-45 ◽  
Author(s):  
Mario Cannataro ◽  
Antonio Congiusta ◽  
Carlo Mastroianni ◽  
Andrea Pugliese ◽  
Domenico Talia ◽  
...  
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Grid Based
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