Results 111 to 120 of about 2,690 (229)
Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window
, 2012 [[abstract]]Mining frequent itemsets has been widely studied over the last decade. Past research focuses on mining frequent itemsets from static databases. In many of the new applications, data flow through the Internet or sensor networks.
C.H. Lin;D.Y. Chiu;Y.H. Wu;A.L.P. Chen
core
A Fuzzy Algorithm for Mining High Utility Rare Itemsets -FHURI
, 2014 Classical frequent itemset mining identifies frequent itemsets in transaction databases using only frequency of item occurrences, without considering utility of items.
Pillai, Jyothi +4 more
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IIS-Mine: A new efficient method for mining frequent itemsets [PDF]
Maejo International Journal of Science and Technology, 2012 A new approach to mine all frequent itemsets from a transaction database isproposed. The main features of this paper are as follows: (1) the proposed algorithmperforms database scanning only once to construct a data structure called an invertedindex ...
Supatra Sahaphong
doaj
Efficient Incremental Mining of Top-K Frequent Closed Itemsets
, 2007 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 ...
PIETRACAPRINA, ANDREA ALBERTO +1 more
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Mining maximal frequent itemsets from data streams
, 2007 Frequent pattern mining from data streams is an active research topic in data mining. Existing research efforts often rely on a two-phase framework to discover frequent patterns: (1) using internal data structures to store meta-patterns obtained by ...
Mao, G, Wu, X, Liu, C, Zhu, X, Chen, G
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Efficient Frequent Itemsets Mining by Sampling
, 2008 . As the first stage for discovering association rules, frequent itemsets mining is an important challenging task for large databases. Sampling provides an efficient way to get approximating answers in much shorter time.
Chengqi Zhang +2 more
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Mining discriminative Itemsets in data streams
, 2014 This paper presents a single pass algorithm for mining discriminative Itemsets in data streams using a novel data structure and the tilted-time window model.
Majid Seyfi +5 more
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Privacy-preserving algorithms for distributed mining of frequent itemsets
, 2006 Standard algorithms for association rule mining are based on identification of frequent itemsets. In this paper, we study how to maintain privacy in distributed mining of fre-quent itemsets.
Sheng Zhong
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Mining Constrained Frequent Itemsets from Distributed Uncertain Data
, 2014 Nowadays, high volumes of massive data can be generated from various sources (e.g., sensor data from environmental surveillance). Many existing distributed frequent itemset mining algorithms do not allow users to express the itemsets to be mined ...
C. K. LEUNG +2 more
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Frequent Itemset Mining for Big Data.
, 2017 Traditional data mining tools, developed to extract actionable knowledge from data, demonstrated to be inadequate to process the huge amount of data produced nowadays. Even the most popular algorithms related to Frequent Itemset Mining, an exploratory data analysis technique used to discover frequent items co-occurrences in a transactional dataset, are
openaire +2 more sources