Discovery of association rules from large databases of item sets is an important data mining problem. Association rules are usually stored in relational databases for future use in decision support systems. In this paper, the problem of asso-ciation rules retrieval and item sets retrieval is recognized as the subset search problem in relational databases. The subset search is not well supported by SQL query language and traditional database indexing techniques. We introduce a new index structure, called Group Bitmap Index, and compare its performance with traditional index-ing methods: B+ tree and bitmap indexes. We show expe-rimentally that proposed index enables faster subset search and significantly outperforms traditional indexing metho...
International audienceThe queries defined on data warehouses are complex and use several join operat...
Generalized association rule mining is an extension of traditional association rule mining to discov...
In this paper we address the problem of finding all association rules in tabular data. An algorithm,...
International audienceStoring sets and querying them (e.g., subset queries that provide all superset...
Abstract. Association rules are among the most popular and widely used data mining techniques. Often...
Storing sets and querying them (e.g., subset queries that provide all supersets of a given set) is k...
Data mining is an important real-life application for businesses. It is critical to find efficient w...
Describe set-oriented algorithms for mining association rules. Such algorithms imply performing mult...
Abstract: The increase in huge amount of data is seen clearly in present days because of requirement...
International audienceThe index selection problem (ISP) concerns the selection of an appropriate ind...
ABSTRACT In this paper a new mining algorithm is defined based on frequent item set. Apriori Algor...
It is very difficult to handle the huge amount of information stored in modern databases. To manage ...
As we all know that association rule is used to find out the rules that are associated with the item...
Compressed bitmap indexes are used to speed up simple aggregate queries in databases. Indeed, set op...
[[abstract]]In this paper, we study the issues of mining and maintaining association rules in a larg...
International audienceThe queries defined on data warehouses are complex and use several join operat...
Generalized association rule mining is an extension of traditional association rule mining to discov...
In this paper we address the problem of finding all association rules in tabular data. An algorithm,...
International audienceStoring sets and querying them (e.g., subset queries that provide all superset...
Abstract. Association rules are among the most popular and widely used data mining techniques. Often...
Storing sets and querying them (e.g., subset queries that provide all supersets of a given set) is k...
Data mining is an important real-life application for businesses. It is critical to find efficient w...
Describe set-oriented algorithms for mining association rules. Such algorithms imply performing mult...
Abstract: The increase in huge amount of data is seen clearly in present days because of requirement...
International audienceThe index selection problem (ISP) concerns the selection of an appropriate ind...
ABSTRACT In this paper a new mining algorithm is defined based on frequent item set. Apriori Algor...
It is very difficult to handle the huge amount of information stored in modern databases. To manage ...
As we all know that association rule is used to find out the rules that are associated with the item...
Compressed bitmap indexes are used to speed up simple aggregate queries in databases. Indeed, set op...
[[abstract]]In this paper, we study the issues of mining and maintaining association rules in a larg...
International audienceThe queries defined on data warehouses are complex and use several join operat...
Generalized association rule mining is an extension of traditional association rule mining to discov...
In this paper we address the problem of finding all association rules in tabular data. An algorithm,...