Results 161 to 170 of about 615 (220)

Optimizing an English text reading recommendation model by integrating collaborative filtering algorithm and FastText classification method. [PDF]

Heliyon
Yan K.
europepmc   +1 more source

Mining summarization of high utility itemsets

Knowledge-Based Systems, 2015
Mining interesting itemsets from transaction databases has attracted a lot of research interests for decades. In recent years, high utility itemset (HUI) has emerged as a hot topic in this field. In real applications, the bottleneck of HUI mining is not at the efficiency but at the interpretability, due to the huge number of itemsets generated by the ...
Zhi-Hong Deng
exaly   +3 more sources

HIGH UTILITY ITEMSETS MINING

International Journal of Information Technology & Decision Making, 2010
High utility itemsets mining identifies itemsets whose utility satisfies a given threshold. It allows users to quantify the usefulness or preferences of items using different values. Thus, it reflects the impact of different items. High utility itemsets mining is useful in decision-making process of many applications, such as retail marketing and Web ...
Ying Liu 0039, Jianwei Li, Wei-keng Liao, Alok N. Choudhary, Yong Shi 0001   +4 more
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Pruning strategies for mining high utility itemsets

Expert Systems With Applications, 2015
Presents an efficient high utility mining method.Employs novel pruning strategies to limit the search space of utility mining.Compares the proposed method against a state-of-the-art utility mining method.Experimentally evaluates the system on eight real and synthetic benchmark datasets.Empirical results are found to be quite promising, especially for ...
Srikumar Krishnamoorthy
exaly   +2 more sources

High-utility and diverse itemset mining

Applied Intelligence, 2021
High-utility Itemset Mining (HUIM) finds patterns from a transaction database with their utility no less than a user-defined threshold. The utility of an itemset is defined as the sum of the utilities of its items. The utility notion enables a data analyst to associate a profit score with each item and thereof to a pattern. We extend the notion of high-
Amit Verma, Siddharth Dawar, Raman Kumar, Shamkant B. Navathe, Vikram Goyal   +4 more
openaire   +1 more source

Mining high utility itemsets

Third IEEE International Conference on Data Mining, 2004
Traditional association rule mining algorithms only generate a large number of highly frequent rules, but these rules do not provide useful answers for what the high utility rules are. We develop a novel idea of top-K objective-directed data mining, which focuses on mining the top-K high utility closed patterns that directly support a given business ...
Raymond Chan, Qiang Yang 0001, Yi-Dong Shen   +2 more
openaire   +1 more source

Mining of high‐utility itemsets with negative utility

Expert Systems, 2018
AbstractHigh‐utility itemset (HUI) mining is an important tasks during data mining. Recently, many algorithms have been proposed to discover HUIs. Most of the algorithms work only for itemsets with positive utility values. However, in the real world, items are found with both positive and negative utility values.
Kuldeep Singh 0003, Harish Kumar Shakya, Abhimanyu Singh, Bhaskar Biswas   +3 more
openaire   +1 more source

Vertical mining for high utility itemsets

2012 IEEE International Conference on Granular Computing, 2012
Recently, high utility itemsets mining becomes one of the most important research issues in data mining due to its ability to consider different profit values for every item. In the past studies, most algorithms generate high utility itemsets from a set of transactions in horizontal data format.
Wei Song 0004, Yu Liu, Jinhong Li
openaire   +1 more source

Mining high average-utility itemsets

2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
The average utility measure is adopted in this paper to reveal a better utility effect of combining several items than the original utility measure. A mining algorithm is then proposed to efficiently find the high average-utility itemsets. It uses the summation of the maximal utility among the items in each transaction including the target itemset as ...
Tzung-Pei Hong, Cho-Han Lee, Shyue-Liang Wang   +2 more
openaire   +1 more source

High average-utility itemsets mining: a survey

Applied Intelligence, 2021
HUIM (High utility itemsets mining) is a sub-division of data mining dealing with the task to obtain promising patterns in the quantitative datasets. A variant of HUIM is to discover the HAUIM (High average-utility itemsets mining) where average-utility measure is used to obtain the utility of itemsets.
Kuldeep Singh 0003, Rajiv Kumar, Bhaskar Biswas   +2 more
openaire   +1 more source