Implementing the information access assistant service for an evaluation

Kaboré, Kiswendsida K.; Sèdes, Florence; Sié, Oumarou; Péninou, André

doi:10.1504/ijitst.2015.073919

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…So professionals are not satisfied with the way how to store big data using internet technologies, but they are trying to analyse this data in a way which is subject to real business needs. However, due to a large amount of digital data available, it is crucial to extract the data corresponding to a most recommended need for information, an application must actually express the need of the end user (Kaboré et al, 2015;Idrissi et al, 2016;Karim et al, 2016). It is, therefore, important to classify the data elements according to their importance (Jomsri et al, 2011), and only the best data items are recovered.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of Topk based on Fagin's algorithm using correlation metrics in cloud computing QoS

Handri

Idrissi

2020

IJITST

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With the exponential growth of cloud computing services recently, several internet technologies began to require the processing of multi-criteria ranking. The collaborative filtering methods and Top k selection computations have been proven to be more effective in information retrieval. In addition, they are widely used to evaluate the QoS for cloud services recommendation. However, the biggest challenge is not only to reduce the size of skyline results, but also to have a good response quality that reflects the user requirement. To deal with these problems, we propose in this paper an approach based on Top k algorithm combined with the weighted sum method. This approach is introduced for refining the skyline result using the Top k query advantages. Then in order to evaluate the performance of our approach, we compared the proposed algorithm with Fagin's one. The experimental results show the efficiency of our algorithm particularly in comparing the runtime results and using specific metrics of correlation.

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