Results 211 to 220 of about 237,412 (261)
Some of the next articles are maybe not open access.
SDS-rules and association rules
Proceedings of the 2004 ACM symposium on Applied computing, 2004The association rule expresses the relation between premise (antecedent) and consequence (succedent). The relation is given by a truth-condition, which can be verified on a given four-fold contingency table denoting the frequencies of objects in some matrix of analyzed data (not-)satisfying antecedent and succedent. This method is more general than the
Tomás Karban, Jan Rauch, Milan Simunek
openaire +1 more source
Mining generalized association rules [PDF]
Future Generation Computer Systems, 1997 Abstract We introduce the problem of mining generalized association rules. Given a large database of transactions, where each transaction consists of a set of items, and a taxonomy (is-a hierarchy) on the items, we find associations between items at any level of the taxonomy.
Ramakrishnan Srikant +1 more
openaire +1 more source
A Rule Format for Associativity
2008We present a new labelled transition system (lts) for the ambient calculus on which ordinary bisimilarity coincides with contextual equivalence. The key feature of this lts is that it is the fruit of ongoing work on developing a systematic procedure for deriving ltss in the structural style from the underlying reduction semantics and observability ...
Sjoerd Cranen +2 more
openaire +2 more sources
2008 IEEE International Conference on Data Mining Workshops, 2008
Action rules describe possible transitions of objects from one state to another with respect to a distinguished attribute. Previous research on action rule discovery usually required the extraction of classification rules before constructing any action rule. This paper gives anew approach for generating association-type action rules.
Zbigniew W. Ras +3 more
openaire +1 more source
Action rules describe possible transitions of objects from one state to another with respect to a distinguished attribute. Previous research on action rule discovery usually required the extraction of classification rules before constructing any action rule. This paper gives anew approach for generating association-type action rules.
Zbigniew W. Ras +3 more
openaire +1 more source
Proceedings 14th International Conference on Data Engineering, 2002
We study the problem of discovering association rules that display regular cyclic variation over time. For example, if we compute association rules over monthly sales data, we may observe seasonal variation where certain rules are true at approximately the same month each year. Similarly, association rules can also display regular hourly, daily, weekly,
Banu Özden +2 more
openaire +1 more source
We study the problem of discovering association rules that display regular cyclic variation over time. For example, if we compute association rules over monthly sales data, we may observe seasonal variation where certain rules are true at approximately the same month each year. Similarly, association rules can also display regular hourly, daily, weekly,
Banu Özden +2 more
openaire +1 more source
Proceedings 13th International Conference on Data Engineering, 2002
The authors consider the problem of clustering two-dimensional association rules in large databases. They present a geometric-based algorithm, BitOp, for performing the clustering, embedded within an association rule clustering system, ARCS. Association rule clustering is useful when the user desires to segment the data. They measure the quality of the
Brian Lent +2 more
openaire +1 more source
The authors consider the problem of clustering two-dimensional association rules in large databases. They present a geometric-based algorithm, BitOp, for performing the clustering, embedded within an association rule clustering system, ARCS. Association rule clustering is useful when the user desires to segment the data. They measure the quality of the
Brian Lent +2 more
openaire +1 more source
Local mining of Association Rules with Rule Schemas
2009 IEEE Symposium on Computational Intelligence and Data Mining, 2009One of the central problems in Knowledge Discovery in Databases, more precisely in the field of Association Rule Mining, relies on the very large number of rules that classic rule mining systems extract. This problem is usually solved by means of a post-processing step, that filters the entire volume of extracted rules, in order to output only a few ...
Andrei Olaru +2 more
openaire +2 more sources
Applied Intelligence, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
Learning Fuzzy Association Rules and Associative Classification Rules
2006 IEEE International Conference on Fuzzy Systems, 2006Learning association rules and/or associative classification rules has been extensively studied in data mining and knowledge discovery community. Associative classification rules are considered as constrained association rules. Mining traditional association rules from transaction databases, however, has suffered some limitations.
openaire +1 more source
Visual Comparison of Association Rules
Computational Statistics, 2001An association rule \(A\to B(\text{supp, conf})\), where ``supp'' is the support and ``conf'' is the confidence of the rule, can be considered as a description of a link between two random events: \(\text{supp}=\Pr(A\cap B)\) and \(\text{conf}=\Pr(B |A)\). The analysis of such rules is aimed at the selection of interesting ones.
Heike Hofmann, Adalbert F. X. Wilhelm
openaire +2 more sources