Investigating web services on the world wide web

By Eyhab Al-Masri, Qusay H. Mahmoud. The Web Conference, 2008

655 citations recorded by the source corpus.

Searching for Web service access points is no longer attached to service registries as Web search engines have become a new major source for discovering Web services. In this work, we conduct a thorough analytical investigation on the plurality of Web service interfaces that exist on the Web today. Using our Web Service Crawler Engine (WSCE), we collect metadata service information on retrieved interfaces through accessible UBRs, service portals and search engines. We use this data to determine Web service statistics and distribution based on object sizes, types of technologies employed, and the number of functioning services. This statistical data can be used to help determine the current status of Web services. We determine an intriguing result that 63% of the available Web services on the Web are considered to be active. We further use our findings to provide insights on improving the service retrieval process.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/caae3e5d73c464fdc4f22f84b1f67ec7a659b5af

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Citations in the corpus

Distributed QoS Evaluation for Real-World Web Services (2010, background): “Al-Masri et al. [1] release a Web service QoS dataset which is observed by only 1 service user on 2,507 Web services.”
Combining global optimization with local selection for efficient QoS-aware service composition (2009, background): “For more details about this dataset we refer the reader to [3, 4].”
Investigating QoS of Real-World Web Services (2014, background): “Al-Masri and Mahmoud [21] show that more than 53 percent of the UDDI business registry registered services are invalid.”
Temporal QoS-aware web service recommendation via non-negative tensor factorization (2014, neutral): “In [1], a Web service QoS dataset is released, which is observed by one service user on 2,507 Web services.”
Cloud computing service composition: A systematic literature review (2014, methodology): “The QWS dataset (Al-Masri & Mahmoud, 2008) and Synthetic Generator (Wang, Sun, & Yang, 2010) are used to evaluate the algorithms.”
Selecting skyline services for QoS-based web service composition (2010, methodology): “More details about this dataset can be found in [1].”