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Erschienen in:
2019 | OriginalPaper | Buchkapitel
The Use of Unified Activity Records to Predict Requests Made by Applications for External Services
verfasst von : Maciej Grzenda, Robert Kunicki, Jaroslaw Legierski
Erschienen in: Intelligent Data Engineering and Automated Learning – IDEAL 2019
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Abstract
Many modern applications use services and data made available by provisioning platforms of third parties. The question arises if the use of individual services and data resources such as open data by novel applications can be predicted. In particular, whether initial software development efforts such as application development during hackathons can be monitored to provide data for the models predicting requests submitted to open data platforms and possibly other platforms is not clear.
In this work, we propose an iterative method of transforming request streams into activity records. By activity records, vectors containing aggregated representation of the requests for external services made by individual applications over growing periods of software development are meant. The approach we propose extends previous works on the development of network flows aggregating network traffic and makes it possible to predict future requests made to web services with high accuracy.