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A-priori is an influence algorithm for finding frequent item sets from association rules. But there are two hard questions may be involved for average users during finding frequent candidates. One question is massive amounts of candidates and the other is that set support count threshold for every level candidate generations. This paper discusses one algorithm called And, which is usually used in...
This paper proposes three novel laws for finding useful candidates in database and preventing useless candidates by researching frequent itemset support. Some new concepts are introduced so as to explain these three laws. For example, independent itemset and support count, which can effectively avoid losing any interest associational rules during pruning, are introduced. In this paper, firstly, some...
A new association rule algorithm is discussed. It is based on the weighted association rule algorithms of minwal(0) and minwal(w). The new algorithm can effectively mine the association rules which define some attributes as antecedent partial, while others as consequent partial. The new algorithm also can effectively mine the association rules with lower support and high confidence, and these association...
Intrusion detection is one of network security area of technology main research directions. Data mining technology was applied to network intrusion detection system (NIDS), may automatically discover the new pattern from the massive network data, to reduce the workload of the manual compilation intrusion behavior patterns and normal behavior patterns. This article reviewed the current intrusion detection...
Currently those algorithms to mine the alarm association rules are limited to the minimal support, so that they can only obtain the association rules among the frequently occurring alarms. This paper proposes a new mining algorithm based on spectral graph theory. The algorithms firstly sets up alarm association model with time series; Secondly, it regards alarms database as a high-dimensional structure...
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