ALGORITHM FOR FINDING MAXIMAL FREQUENT SETS

Algorithm for Finding Maximal Frequent Sets

Given a set X and a set C of subsets of X, subsets of X covered by k sets in C are called k-frequent. Frequent sets are of interest in large scale data analysis, pattern recognition and data mining. Characterization of maximal kfrequent sets in terms of equivalence relation and partial order is given. A general algorithm for finding maximal k-frequent sets, efficient for wide range of practical...

Finding Frequent Subgraphs in Biological Networks Via Maximal Item Sets

An Efficient Algorithm for Mining Maximal Frequent Item Sets

Problem Statement: In today’s life, the mining of frequent patterns is a basic problem in data mining applications. The algorithms which are used to generate these frequent patterns must perform efficiently. The objective was to propose an effective algorithm which generates frequent patterns in less time. Approach: We proposed an algorithm which was based on hashing technique and combines a ve...

Finding All Maximal Frequent Sequences in Text

In this paper we present a novel algorithm for discovering maximal frequent sequences in a set of documents, i.e., such sequences of words that are frequent in the document collection and, moreover, that are not contained in any other longer frequent sequence. A sequence is considered to be frequent if it appears in at least documents, when is the frequency threshold given. Our approach combine...

LPMiner : An Algorithm for Finding Frequent

Over the years, a variety of algorithms for nding frequent itemsets in very large transaction databases have been developed. The key feature in most of these algorithms is that they use a constant support constraint to control the inherently exponential complexity of the problem. In general, itemsets that contain only a few items will tend to be interesting if they have a high support, whereas ...