An On-Line Approximation Algorithm for Mining Frequent Closed Itemsets Based on Incremental Intersection
نویسندگان
چکیده
We propose a new on-line ε-approximation algorithm for mining closed itemsets from a transactional data stream, which is also based on the incremental/cumulative intersection principle. The proposed algorithm, called LC-CloStream, is constructed by integrating CloStream algorithm and Lossy Counting algorithm. We investigate some behaviors of the LC-CloStream algorithm. Firstly we show the incompleteness and the semi-completeness for mining all frequent closed itemsets in a stream. Next, we give the completeness of εapproximation for extracting frequent itemsets.
منابع مشابه
DBV-Miner: A Dynamic Bit-Vector approach for fast mining frequent closed itemsets
Frequent closed itemsets (FCI) play an important role in pruning redundant rules fast. Therefore, a lot of algorithms for mining FCI have been developed. Algorithms based on vertical data formats have some advantages in that they require scan databases once and compute the support of itemsets fast. Recent years, BitTable (Dong & Han, 2007) and IndexBitTable (Song, Yang, & Xu, 2008) approaches h...
متن کاملOptimization Of Intersecting Algorithm For Transactions Of Closed Frequent Item Sets In Data Mining
Data mining is the computer-assisted process of information analysis. Mining frequent itemsets is a fundamental task in data mining. Unfortunately the number of frequent itemsets describing the data is often too large to comprehend. This problem has been attacked by condensed representations of frequent itemsets that are sub collections of frequent itemsets containing only the frequent itemsets...
متن کاملAn Efficient Incremental Algorithm to Mine Closed Frequent Itemsets over Data Streams
The purpose of this work is to mine closed frequent itemsets from transactional data streams using a sliding window model. An efficient algorithm IMCFI is proposed for Incremental Mining of Closed Frequent Itemsets from a transactional data stream. The proposed algorithm IMCFI uses a data structure called INdexed Tree(INT) similar to NewCET used in NewMoment[5]. INT contains an index table Item...
متن کاملIncremental updates of closed frequent itemsets over continuous data streams
Online mining of closed frequent itemsets over streaming data is one of the most important issues in mining data streams. In this paper, we propose an efficient one-pass algorithm, NewMoment to maintain the set of closed frequent itemsets in data streams with a transaction-sensitive sliding window. An effective bit-sequence representation of items is used in the proposed algorithm to reduce the...
متن کاملEfficient Incremental Mining of Top-K Frequent Closed Itemsets
In this work we study the mining of top-K frequent closed itemsets, a recently proposed variant of the classical problem of mining frequent closed itemsets where the support threshold is chosen as the maximum value sufficient to guarantee that the itemsets returned in output be at least K. We discuss the effectiveness of parameter K in controlling the output size and develop an efficient algori...
متن کامل