Add to ORKGInternational audienceA main challenge in pattern mining is to focus the discovery on high-quality patterns. One popular solution is to compute a numerical score on how well each discovered pattern describes the data. The best rating patterns are then the most analyzed by the data expert. In this paper, we evaluate the quality of discovered patterns by anticipating of how user analyzes them. We show that the examination of frequent patterns with the notion of support led to an unbalanced analysis of the dataset. Certain transactions are indeed completely ignored. Hence, we propose the notion of balanced support that weights the transactions to let each of them receive user specified attention. We also develop an algorithm Absolute for calcu...
Mining Frequent Itemsets is the core operation of many data mining algorithms. This operation howeve...
International audienceHow can one determine whether a data mining method ex- tracts interesting patt...
There have been many studies on efficient discovery of frequent patterns in large databases. The usu...
Traditional association mining algorithms use a strict definition of support that requires every ite...
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, t...
Deriving useful and interesting rules from a data mining system is an essential and important task. ...
Data mining, or knowledge discovery in databases, aims at finding useful regularities in large data ...
Within data mining, the efficient discovery of frequent patterns—sets of items that occur together ...
Itemset mining approaches, while having been studied for more than 15 years, have been evaluated onl...
International audienceFrequent-Regular pattern mining has been introduced to extract interesting pat...
Frequent pattern mining is an important data mining problem with wide applications. The huge number ...
The recent studies of pattern mining have given more attention to discovering patterns that are inte...
Itemset mining approaches, while having been studied for more than 15 years, have been evaluated onl...
We present an overview of data mining techniques for extracting knowledge from large databases with ...
Abstract. Mining user profiles is a crucial task for Web usage mining, and can be accomplished by mi...
Mining Frequent Itemsets is the core operation of many data mining algorithms. This operation howeve...
International audienceHow can one determine whether a data mining method ex- tracts interesting patt...
There have been many studies on efficient discovery of frequent patterns in large databases. The usu...
Traditional association mining algorithms use a strict definition of support that requires every ite...
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, t...
Deriving useful and interesting rules from a data mining system is an essential and important task. ...
Data mining, or knowledge discovery in databases, aims at finding useful regularities in large data ...
Within data mining, the efficient discovery of frequent patterns—sets of items that occur together ...
Itemset mining approaches, while having been studied for more than 15 years, have been evaluated onl...
International audienceFrequent-Regular pattern mining has been introduced to extract interesting pat...
Frequent pattern mining is an important data mining problem with wide applications. The huge number ...
The recent studies of pattern mining have given more attention to discovering patterns that are inte...
Itemset mining approaches, while having been studied for more than 15 years, have been evaluated onl...
We present an overview of data mining techniques for extracting knowledge from large databases with ...
Abstract. Mining user profiles is a crucial task for Web usage mining, and can be accomplished by mi...
Mining Frequent Itemsets is the core operation of many data mining algorithms. This operation howeve...
International audienceHow can one determine whether a data mining method ex- tracts interesting patt...
There have been many studies on efficient discovery of frequent patterns in large databases. The usu...