Results 11 to 20 of about 45,837 (241)
A Privacy Frequent Itemsets Mining Framework for Collaboration in IoT Using Federated Learning
ACM Trans. Sens. Networks, 2022 Rapid advancement of industrial internet of things (IoT) technology has changed the supply chain network to an open system to meet the high demand for individualized products and provide better customer experiences.
J. Wu +4 more
semanticscholar +1 more source
Efficient mining of intra-periodic frequent sequences
Array, 2022 Frequent Sequence Mining (FSM) is a fundamental task in data mining. Although FSM algorithms extract frequent patterns, they cannot discover patterns that periodically appear in the data.
Edith Belise Kenmogne +4 more
doaj +1 more source
Weighted Frequent Itemsets Mining Algorithm Based on Difference Nodeset [PDF]
Jisuanji gongcheng, 2020 To address the low mining efficiency of NFWI,a WN-list based algorithm for weighted frequent itemsets mining,this paper proposes a WDiffNodeset-based weighted frequent itemsets mining algorithm,DiffNFWI.The algorithm extends the data structure of ...
WANG Bin, FANG Xinxiu, WEI Tianyou
doaj +1 more source
Association Mining for Super Market Sales using UP Growth and Top-K Algorithm [PDF]
ITM Web of Conferences, 2020 Frequent itemsets(HUIs) mining is an evolving field in data mining, that centers around finding itemsets having a utility that meets a user-specified minimum utility by finding all the itemsets.
Bhope Harshal +3 more
doaj +1 more source
IEEE Access, 2021 One of the most challenging tasks in association rule mining is that when a new incremental database is added to an original database, some existing frequent itemsets may become infrequent itemsets and vice versa.
Wannasiri Thurachon, Worapoj Kreesuradej
doaj +1 more source
Sliding Window-based Frequent Itemsets Mining over Data Streams using Tail Pointer Table [PDF]
International Journal of Computational Intelligence Systems, 2014 Mining frequent itemsets over transaction data streams is critical for many applications, such as wireless sensor networks, analysis of retail market data, and stock market predication.
Le Wang, Lin Feng, Bo Jin
doaj +1 more source
On differentially private frequent itemset mining [PDF]
Proceedings of the VLDB Endowment, 2012 We consider differentially private frequent itemset mining. We begin by exploring the theoretical difficulty of simultaneously providing good utility and good privacy in this task. While our analysis proves that in general this is very difficult, it leaves a glimmer of hope in that our proof of difficulty relies on the existence of long ...
Chen, Zeng +2 more
openaire +2 more sources
MAXLEN-FI: AN ALGORITHM FOR MINING MAXIMUM- LENGTH FREQUENT ITEMSETS FAST
Tạp chí Khoa học Đại học Đà Lạt, 2018 Association rule mining, one of the most important and well-researched techniques of data mining. Mining frequent itemsets are one of the most fundamental and most time-consuming problems in association rule mining.
Phan Thành Huấn, Lê Hoài Bắc
doaj +1 more source
Memory-efficient frequent-itemset mining
Proceedings of the 14th International Conference on Extending Database Technology, 2011 Efficient discovery of frequent itemsets in large datasets is a key component of many data mining tasks. In-core algorithms---which operate entirely in main memory and avoid expensive disk accesses---and in particular the prefix tree-based algorithm FP-growth are generally among the most efficient of the available algorithms.
Schlegel, Benjamin +2 more
openaire +3 more sources
Mining All Non-derivable Frequent Itemsets [PDF]
, 2002 3 ...
Calders, T., GOETHALS, Bart
openaire +5 more sources