Results 91 to 100 of about 1,488,653 (205)
IEEE AccessData analytics is an integral part of strategic decision making in various fields but not limited to business, education and healthcare systems. Existing research works focus on the discovery of itemsets with rare antecedents and consequent or frequent ...
Shwetha Rai +4 more
doaj +1 more source
An Efficient Algorithm for Frequent Pattern Mining for Real-Time Business Intelligence Analytics in Dense Datasets [PDF]
Finding frequent patterns from databases has been the most time consuming process in data mining tasks, like association rule mining. Frequent pattern mining in real-time is of increasing thrust in many business applications such as e-commerce ...
Dass, Rajanish
core
Fast mining frequent itemsets using Nodesets
, 2014 Node-list and N-list, two novel data structure proposed in recent years, have been proven to be very efficient for mining frequent itemsets. The main problem of these structures is that they both need to encode each node of a PPC-tree with pre-order and ...
Lv, Sheng-Long, Deng, Zhi-Hong
core +1 more source
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
Fast Distributed Algorithm of Mining Global Frequent Itemsets
, 2011 Most distributed algorithms of mining global frequent itemsets worked on net structure network and adopted Apriori-like algorithm. Whereas there were some problems in these algorithms: a lot of candidate itemsets and heavy communication traffic.
Bo He
core +1 more source
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
core
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
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
core
maintaining only frequent itemsets to mine approximate frequent itemsets over online data streams
, 2009 IEEEMining frequent itemsets over online data streams, where the new data arrive and the old data will be removed with high speed, is a challenge for the computational complexity.
Li Kun, Wang Hongan, Wang Yongyan
core +1 more source