ARIMA Model-Based Web Services Trustworthiness Evaluation and Prediction [chapter]

Meng Li, Zhebang Hua, Junfeng Zhao, Yanzhen Zou, Bing Xie
<span title="">2012</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
As most Web services are delivered by third parties over unreliable Internet and are late bound at run-time, it is reasonable and useful to evaluate and predict the trustworthiness of Web services. In this paper, we propose an ARIMA model-based approach to evaluate and predict Web services trustworthiness. First, we evaluate Web services trustworthiness with comprehensive trustworthy evidences collected from the Internet on a regular basis. Then, the cumulative trustworthiness evaluation
more &raquo; ... are modeled as time series. Finally, we propose an ARIMA model-based multi-step Web services trustworthiness prediction process, which can automatically and iteratively identify and optimize the model to fit the trustworthiness series data. Experiments conducted on a large-scale real-world data set show that our method can effectively evaluate and predict the trustworthiness of Web services, which helps users to reuse Web services.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-34321-6_51">doi:10.1007/978-3-642-34321-6_51</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eepplzavt5bpxeiwcatvvtni2e">fatcat:eepplzavt5bpxeiwcatvvtni2e</a> </span>
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