Results 281 to 290 of about 25,851 (312)

A Bayesian Association Rule Mining Algorithm

2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013
This paper proposes a Bayesian association rule mining algorithm (BAR) which combines the Apriori association rule mining algorithm with Bayesian networks. Two interestingness measures of association rules: Bayesian confidence (BC) and Bayesian lift (BL) which measure conditional dependence and independence relationships between items are defined based
David Tian, Ann Gledson, Athos Antoniades, Aristos Aristodimou, Dimitrios Ntalaperas, Ratnesh Sahay, Jianxin Pan, Stavros Stivaros, Goran Nenadic, Xiao-Jun Zeng, John A. Keane   +10 more
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Mining Vague Association Rules

2007
In many online shopping applications, traditional Association Rule (AR) mining has limitations as it only deals with the items that are sold but ignores the items that are almost sold. For example, those items that are put into the basket but not checked out.
An Lu, Yiping Ke, James Cheng, Wilfred Ng   +3 more
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Efficient mining of intertransaction association rules

IEEE Transactions on Knowledge and Data Engineering, 2003
Most of the previous studies on mining association rules are on mining intratransaction associations, i.e., the associations among items within the same transaction where the notion of the transaction could be the items bought by the same customer, the events happened on the same day, etc.
Tung, Anthony Kum Hoe, Lu, Hongjun, Han, Jiawei, Feng, Ling   +3 more
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Mining Strongly Associated Rules

2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
One of the main tasks of KDTCM (knowledge discovery in Traditional Chinese Medicine) is discovering novel paired or grouped drugs from Chinese Medical Formula Database. Paired or grouped drugs, which are special combinations of two or more drugs? have strong efficacy.
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Mining Indirect Association Rules

2004
A large database, such as POS data, could give us many insights about customer behavior. Many techniques and measures have been proposed to extract interesting rules. As the study of Association rule mining has proceeded, the rules about items that are not bought together at the same transaction have been regarded as important.
Shinichi Hamano, Masako Sato
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An Extension to SQL for Mining Association Rules

Data Mining and Knowledge Discovery, 1998
Data mining evolved as a collection of applicative problems and efficient solution algorithms relative to rather peculiar problems, all focused on the discovery of relevant information hidden in databases of huge dimensions. In particular, one of the most investigated topics is the discovery of association rules.
Meo, Rosa, Psaila, Giuseppe, Ceri, Stefano   +2 more
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Association Rule Mining I

2013
This chapter looks at the problem of finding any rules of interest that can be derived from a given dataset, not just classification rules as before. This is known as Association Rule Mining or Generalised Rule Induction. A number of measures of rule interestingness are defined and criteria for choosing between measures are discussed.
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A Survey of Association-Rule Mining

2000
The standard model for association-rule mining involves a set of "items" and a set of "baskets." The baskets contain items that some customer has purchased at the same time. The problem is to find pairs, or perhaps larger sets, of items that frequently appear together in baskets.
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A comprehensive review of visualization methods for association rule mining: Taxonomy, challenges, open problems and future ideas

Expert Systems With Applications, 2023
Iztok Fister, Dusan Fister, Vili Podgorelec   +2 more
exaly  

A Systematic Assessment of Numerical Association Rule Mining Methods

SN Computer Science, 2021
Minakshi Kaushik, Rahul Sharma, Sijô Arakkal Peious   +2 more
exaly