scholarly journals Frequent Pattern Mining Approach for a Mobile Web Service Environment Using Service Utility

Author(s):  
Krishna Kumar Mohbey
2018 ◽  
Vol 11 (2) ◽  
pp. 31-52
Author(s):  
Krishna Kumar Mohbey

This article describes how patterns discovery of mobile web services is an emerging field today, in which utility also plays an important role. Utility may be referred to as profit, price, significance or preference of the mobile web services. With the help of web utility, one can discover highly interesting patterns of mobile web services. In the previous related studies, most of the approaches use utility as an important parameter to discover interesting patterns, but they also generate a large number of uninterested patterns too. Another problem is related to computational time; because no filtration is applied therefore computational time is too much. In this article, an approach namely; UMWSPM (Utility based Mobile Web Service Pattern Mining) for finding utility-based mobile web service patterns with high filtration and less computational time has been proposed. In this article, a utility is used as the preference of the accessed mobile web services. In particular, the proposed approach obtains more accurate and filtered mobile web service sequences. The experimental results show that the proposed approach has a good performance in terms of execution efficiency and memory utilization.


Information sharing among the associations is a general development in a couple of zones like business headway and exhibiting. As bit of the touchy principles that ought to be kept private may be uncovered and such disclosure of delicate examples may impacts the advantages of the association that have the data. Subsequently the standards which are delicate must be secured before sharing the data. In this paper to give secure information sharing delicate guidelines are bothered first which was found by incessant example tree. Here touchy arrangement of principles are bothered by substitution. This kind of substitution diminishes the hazard and increment the utility of the dataset when contrasted with different techniques. Examination is done on certifiable dataset. Results shows that proposed work is better as appear differently in relation to various past strategies on the introduce of evaluation parameters.


2011 ◽  
Vol 22 (8) ◽  
pp. 1749-1760
Author(s):  
Yu-Hong GUO ◽  
Yun-Hai TONG ◽  
Shi-Wei TANG ◽  
Leng-Dong WU

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1160
Author(s):  
Atsuko Okazaki ◽  
Sukanya Horpaopan ◽  
Qingrun Zhang ◽  
Matthew Randesi ◽  
Jurg Ott

Some genetic diseases (“digenic traits”) are due to the interaction between two DNA variants, which presumably reflects biochemical interactions. For example, certain forms of Retinitis Pigmentosa, a type of blindness, occur in the presence of two mutant variants, one each in the ROM1 and RDS genes, while the occurrence of only one such variant results in a normal phenotype. Detecting variant pairs underlying digenic traits by standard genetic methods is difficult and is downright impossible when individual variants alone have minimal effects. Frequent pattern mining (FPM) methods are known to detect patterns of items. We make use of FPM approaches to find pairs of genotypes (from different variants) that can discriminate between cases and controls. Our method is based on genotype patterns of length two, and permutation testing allows assigning p-values to genotype patterns, where the null hypothesis refers to equal pattern frequencies in cases and controls. We compare different interaction search approaches and their properties on the basis of published datasets. Our implementation of FPM to case-control studies is freely available.


2021 ◽  
Vol 1916 (1) ◽  
pp. 012054
Author(s):  
M Kavitha Margret ◽  
A Ponni ◽  
A Priyanka

2021 ◽  
Vol 169 ◽  
pp. 114530
Author(s):  
Areej Ahmad Abdelaal ◽  
Sa'ed Abed ◽  
Mohammad Al-Shayeji ◽  
Mohammad Allaho

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