Cloud computing is promoting the computing worldview in which information is outsourced to an outsider specialist third party server for data mining. Outsourcing raises a genuine security and correctness issue in what manner the customer of weak computational power can confirm that the server returned ...
There is a large body of research on Frequent Itemset Mining (FIM) but very little work addresses FIM in uncertain databases. Most studies on frequent itemset mining focus on mining precise data. However, there are situations in which the data are uncertain. This leads to the mining of ...
Frequent Itemset search is needed as a part of association mining in Data mining research field of Machine Learning. This code gives you upto the frequent k-itemset as output. You may want to change two things in MAIN file as per your need: First one is 'A': the input matrix with ...
Cloud computing is popularizing the computing paradigm in which data is outsourced to a third-party service provider (server) for data mining. Outsourcing, however, raises a serious security issue: how can the client of weak computational power verify that the server returned correct mining result?
Recently, many enchanced Apriori algorithms have been proposed to efficiently generate all frequent itemsets from datasets in data mining field. Although efficient techniques were presented, those algorithms are either time-consuming or memory-consuming. To address the issue further, a new algorithm, wh...
Mining frequent item set (FI) is an important issue in data mining. Considering the limitations of those exact algorithms and sampling methods, a novel FI mining algorithm based on granular computing and fuzzy set theory (FI-GF) is proposed, which mines those datasets with high number of trans...
The discovery of frequent itemsets is one of the very important topics in data mining. Frequent itemset discovery techniques help in generating qualitative knowledge which gives business insight and helps the decision makers. In the Big ... MA Gawwad,MF Ahmed,MB Fayek - 《Data Science Journal》...
With the explosive growth of data stored in electronic form, data mining has become essential in searching nontrivial, implicit, previously unknown and potentially useful information from a huge amount of data. Association rule mining in large transactional databases is an important topic in the field...
ing the frequencies of many itemsets at once in short time. In an iteration of mining algorithms, some candidate item- sets are generated, and their frequencies are computed. The occurrence deliver stores the transaction database by ar-
we give the first application of our declarative framework in data mining, namely, the problem of enumerating the Top-kfrequent closed itemsets of length at leastmin(FCIMmink). Finally, to show the nice declarative aspects of our framework, we encode several other variants ofFCIMminkinto the ...