Time Aware Mining of Itemsets

10 years 4 months ago
Time Aware Mining of Itemsets
Frequent behavioural pattern mining is a very important topic of knowledge discovery, intended to extract correlations between items recorded in large databases or Web acces logs. However, those databases are usually considered as a whole and hence, itemsets are extracted over the entire set of records. Our claim is that possible periods, hidden within the structure of the data and containing compact itemsets, may exist. These periods, as well as the itemsets they contain, might not be found by traditional data mining methods due to their very weak support. Furthermore, these periods might be lost depending on an arbitrary division of the data. The goal of our work is to find itemsets that are frequent over a specific period but would not be extracted by traditional methods since their support is very low over the whole dataset. In this paper, we introduce the definition of solid itemsets, which represent a coherent and compact behavior over a specific period, and we propose SIM, ...
Bashar Saleh, Florent Masseglia
Added 01 Jun 2010
Updated 01 Jun 2010
Type Conference
Year 2008
Where TIME
Authors Bashar Saleh, Florent Masseglia
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