Model-based probabilistic frequent itemset mining
نویسندگان
چکیده
منابع مشابه
Mining Frequent Sequences Using Itemset-Based Extension
In this paper, we systematically explore an itemset-based extension approach for generating candidate sequence which contributes to a better and more straightforward search space traversal performance than traditional item-based extension approach. Based on this candidate generation approach, we present FINDER, a novel algorithm for discovering the set of all frequent sequences. FINDER is compo...
متن کاملProbabilistic Frequent Pattern Growth for Itemset Mining in Uncertain Databases
Frequent itemset mining in uncertain transaction databases semantically and computationally di ers from traditional techniques applied on standard (certain) transaction databases. Uncertain transaction databases consist of sets of existentially uncertain items. The uncertainty of items in transactions makes traditional techniques inapplicable. In this paper, we tackle the problem of nding proba...
متن کاملProbabilistic Frequent Itemset Mining on a GPU Cluster
Probabilistic frequent itemset mining, which discovers frequent itemsets from uncertain data, has attracted much attention due to inherent uncertainty in the real world. Many algorithms have been proposed to tackle this problem, but their performance is not satisfactory because handling uncertainty incurs high processing cost. To accelerate such computation, we utilize GPUs (Graphics Processing...
متن کاملGrafting for Combinatorial Boolean Model using Frequent Itemset Mining
is paper introduces the combinatorial Booleanmodel (CBM), which is defined as the class of linear combinations of conjunctions of Boolean aributes. is paper addresses the issue of learning CBM from labeled data. CBM is of high knowledge interoperability but naı̈ve learning of it requires exponentially large computation time with respect to data dimension and sample size. To overcome this comp...
متن کاملFrequent Itemset Mining Using Rough-Sets
Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cro...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Knowledge and Information Systems
سال: 2012
ISSN: 0219-1377,0219-3116
DOI: 10.1007/s10115-012-0561-2