Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking
To accurately rank various web services can be a very challenging task depending on the evaluation criteria used, however, it can play an important role in performing a better selection of web services afterward. This paper proposes an approach to evaluate trust prediction and confusion matrix to ra...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9091880/ |
| _version_ | 1818663855244443648 |
|---|---|
| author | Muhammad Hasnain Muhammad Fermi Pasha Imran Ghani Muhammad Imran Mohammed Y. Alzahrani Rahmat Budiarto |
| author_facet | Muhammad Hasnain Muhammad Fermi Pasha Imran Ghani Muhammad Imran Mohammed Y. Alzahrani Rahmat Budiarto |
| author_sort | Muhammad Hasnain |
| collection | DOAJ |
| description | To accurately rank various web services can be a very challenging task depending on the evaluation criteria used, however, it can play an important role in performing a better selection of web services afterward. This paper proposes an approach to evaluate trust prediction and confusion matrix to rank web services from throughput and response time. AdaBoostM1 and J48 classifiers are used as binary classifiers on a benchmark web services dataset. The trust score (TS) measuring method is proposed by using the confusion matrix to determine trust scores of all web services. Trust prediction is calculated using 5-Fold, 10-Fold, and 15-Fold cross-validation methods. The reported results showed that the web service 1 (WS1) was most trusted with (48.5294%) TS value, and web service 2 (WS2) was least trusted with (24.0196%) TS value by users. Correct prediction of trusted and untrusted users in web services invocation has improved the overall selection process in a pool of similar web services. Kappa statistics values are used for the evaluation of the proposed approach and for performance comparison of the two above-mentioned classifiers. |
| first_indexed | 2024-12-17T05:23:28Z |
| format | Article |
| id | doaj.art-f551044e9b694299a8d15b937b9fa53e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T05:23:28Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f551044e9b694299a8d15b937b9fa53e2022-12-21T22:01:56ZengIEEEIEEE Access2169-35362020-01-018908479086110.1109/ACCESS.2020.29942229091880Evaluating Trust Prediction and Confusion Matrix Measures for Web Services RankingMuhammad Hasnain0https://orcid.org/0000-0002-8632-0528Muhammad Fermi Pasha1https://orcid.org/0000-0002-9848-8950Imran Ghani2Muhammad Imran3https://orcid.org/0000-0002-4124-7929Mohammed Y. Alzahrani4https://orcid.org/0000-0002-9726-6088Rahmat Budiarto5https://orcid.org/0000-0002-6374-4731School of IT, Monash University Malaysia, Subang Jaya, MalaysiaSchool of IT, Monash University Malaysia, Subang Jaya, MalaysiaDepartment of Mathematics and Computer Sciences, Indiana University of Pennsylvania, Indiana, PA, USANext Bridge (Pvt.) Ltd., Lahore, PakistanInformation Technology Department, College of Computer Science and IT, Albaha University, Al Bahah, Saudi ArabiaComputer Engineering and Science Department, College of Computer Science and IT, Albaha University, Al Bahah, Saudi ArabiaTo accurately rank various web services can be a very challenging task depending on the evaluation criteria used, however, it can play an important role in performing a better selection of web services afterward. This paper proposes an approach to evaluate trust prediction and confusion matrix to rank web services from throughput and response time. AdaBoostM1 and J48 classifiers are used as binary classifiers on a benchmark web services dataset. The trust score (TS) measuring method is proposed by using the confusion matrix to determine trust scores of all web services. Trust prediction is calculated using 5-Fold, 10-Fold, and 15-Fold cross-validation methods. The reported results showed that the web service 1 (WS1) was most trusted with (48.5294%) TS value, and web service 2 (WS2) was least trusted with (24.0196%) TS value by users. Correct prediction of trusted and untrusted users in web services invocation has improved the overall selection process in a pool of similar web services. Kappa statistics values are used for the evaluation of the proposed approach and for performance comparison of the two above-mentioned classifiers.https://ieeexplore.ieee.org/document/9091880/Web servicestrust predictionweb services selectionbinary classificationfuzzy rulesconfusion matrix |
| spellingShingle | Muhammad Hasnain Muhammad Fermi Pasha Imran Ghani Muhammad Imran Mohammed Y. Alzahrani Rahmat Budiarto Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking IEEE Access Web services trust prediction web services selection binary classification fuzzy rules confusion matrix |
| title | Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking |
| title_full | Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking |
| title_fullStr | Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking |
| title_full_unstemmed | Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking |
| title_short | Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking |
| title_sort | evaluating trust prediction and confusion matrix measures for web services ranking |
| topic | Web services trust prediction web services selection binary classification fuzzy rules confusion matrix |
| url | https://ieeexplore.ieee.org/document/9091880/ |
| work_keys_str_mv | AT muhammadhasnain evaluatingtrustpredictionandconfusionmatrixmeasuresforwebservicesranking AT muhammadfermipasha evaluatingtrustpredictionandconfusionmatrixmeasuresforwebservicesranking AT imranghani evaluatingtrustpredictionandconfusionmatrixmeasuresforwebservicesranking AT muhammadimran evaluatingtrustpredictionandconfusionmatrixmeasuresforwebservicesranking AT mohammedyalzahrani evaluatingtrustpredictionandconfusionmatrixmeasuresforwebservicesranking AT rahmatbudiarto evaluatingtrustpredictionandconfusionmatrixmeasuresforwebservicesranking |