FIMI
2004
13 years 10 months ago
2004
Frequency mining problem comprises the core of several data mining algorithms. Among frequent pattern discovery algorithms, FP-GROWTH employs a unique search strategy using compac...
FIMI
2004
13 years 10 months ago
2004
One of the main problems raising up in the frequent closed itemsets mining problem is the duplicate detection. In this paper we propose a general technique for promptly detecting ...
FIMI
2004
13 years 10 months ago
2004
In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
FIMI
2004
13 years 10 months ago
2004
Implementations of the well-known Apriori algorithm for finding frequent item sets and associations rules usually rely on a doubly recursive scheme to count the subsets of a given...
FIMI
2004
13 years 10 months ago
2004
Trie is a popular data structure in frequent itemset mining (FIM) algorithms. It is memory-efficient, and allows fast construction and information retrieval. Many trie-related tec...
DMIN
2006
13 years 10 months ago
2006
Data mining, with its promise to extract valuable, previously unknown and potentially useful patterns or knowledge from large data sets that contain private information is vulnerab...
ESANN
2004
13 years 10 months ago
2004
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
CATE
2004
13 years 10 months ago
2004
Recently web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations...
APVIS
2006
13 years 10 months ago
2006
Evidence-based medicine (EBM) is a shift in which medicine from being based on individual experience of doctors to evidence with clear background. In this shift, data mining can p...
APCCM
2006
13 years 10 months ago
2006
Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of `emergent' patterns and tre...