Classic algorithms for sequential pattern discovery, return all frequent sequences present in a database. Since, in general, only a few ones are interesting from a user's poin...
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
In this paper we consider the problem of discovering frequent temporal patterns in a database of temporal sequences, where a temporal sequence is a set of items with associated da...
: Relational representation of objects using graphs reveals much information that cannot be obtained by attribute value representations alone. There are already many databases that...
This paper presents a systematic approach to mine colocation patterns in Sloan Digital Sky Survey (SDSS) data. SDSS Data Release 5 (DR5) contains 3.6 TB of data. Availability of s...