Abstract
With the rapid expansion of services on the Internet, Mashup development has become a trend toward mainstream development. How to efficiently and quickly discover available services in Mashup development and make full use of existing services to meet the changing needs of users has become a new concern. Although there are a lot of work for service discovery, there are still some problems in the existing methods, such as limiting the service description to a single structured document, limiting the service search statement to keywords, and rarely mining the deeper semantics of the service text. information. In view of the above problems, this paper proposes the Service Discovery approach for Agile Mashup Development (SDAMD), which breaks the limitation of the single document and drives the user story in agile development as a service search. The original text, through the natural language processing technology, extracts the three elements of agile requirements, and then extracts the three service attributes of the agile service; then finds and recommends similar services by calculating the similarity between the service description and the search text. This article uses the real data of the services on the Programmable Web to verify the validity of SDAMD.
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References
Majchrzak, A., More, P.H.B.: Emergency! web 2.0 to the rescue! J. Commun. ACM 54(4), 125 (2011). https://doi.org/10.1145/1924421.1924449
Shi, M., Liu, J., Zhou, D., Tang, Y.: A topic-sensitive method for mashup tag recommendation utilizing multi-relational service data. J. IEEE Trans. Servi. Comput. 1, (2018). https://doi.org/10.1109/tsc.2018.2805826
Xing, Z., Shijun, L.I., Wei, Y.U., Sha, Y., Yonggang, D., Yahui, H.U., et al.: Research on web data source quality assessment method in big data. J. Comput. Eng. 43, 48–56 (2017)
Zhou, N., Xie, J.Y.: Select web services based on qualitative multi-users preferences. J. Acta Electronica Sinica 39(4), 729–736 (2011). https://doi.org/10.1016/j.cageo.2010.07.006
Lin, J., Yu, H., Shen, Z., Miao, C.: Using goal net to model user stories in agile software development (2014). https://doi.org/10.1109/snpd.2014.6888731
Hui-Ming, Z., Hui-Jia, T.: Research of matching strategy of semantic web services discovery. J. Comput. Appl. (2010). https://doi.org/10.3724/sp.j.1087.2010.01083
Mateos, C., Rodriguez, J.M., Zunino, A.: A tool to improve code-first web services discoverability through text mining techniques. J. Softw.: Pract. Exp. 45(7), 925–948 (2015). https://doi.org/10.1002/spe.2268
Haekal, M., Eliyani.: Token-based authentication using JSON web token on SIKASIR RESTful web service. In: International Conference on Informatics & Computing. IEEE (2017). https://doi.org/10.1109/iac.2016.7905711
Yi-Song, L., Yu-Cheng, Y.: Semantic web service discovery based on text clustering and similarity of concepts. J. Comput. Sci. 11, 46 (2013)
Zhang, N., Wang, J., He, K., Li, Z.: An approach of service discovery based on service goal clustering. In: IEEE International Conference on Services Computing IEEE (2016). https://doi.org/10.1109/scc.2016.22
Paliwal, A.V., Shafiq, B., Vaidya, J., Xiong, H., Adam, N.: Semantics-based automated service discovery. J. IEEE Trans. Serv. Comput. 5(2), 260–275 (2012). https://doi.org/10.1109/TSC.2011.19
Roman, D., Kopecký, J., Vitvar, T., Domingue, J., Fensel, D.: WSMO-lite and hRESTS: lightweight semantic annotations for web services and RESTful APIs. J. Web Semant.: Sci. Serv. Agents World Wide Web 31, 39–58 (2015). https://doi.org/10.1016/j.websem.2014.11.006
Deng, S.G., Yin, J.W., Li, Y., Wu, Z.: A method of semantic web service discovery based on bipartite graph matching. J. Chin. J. Comput. 31(8), 1364–1375 (2008). https://doi.org/10.3724/sp.j.1016.2008.01364
Shi, M., Liu, J., Zhou, D., Tang, M., Cao, B.: WE-LDA: a word embeddings augmented LDA model for web services clustering. In: 2017 IEEE International Conference on Web Services (ICWS). IEEE Computer Society (2017). https://doi.org/10.1109/icws.2017.9
Zhong, Y., Fan, Y., Huang, K., Tan, W., Zhang, J.: Time-aware service recommendation for mashup creation in an evolving service ecosystem. In: 2014 IEEE International Conference on Web Services (ICWS). IEEE Computer Society (2014). https://doi.org/10.1109/icws.2014.17
Meng, Y., Rumshisky, A., Romanov, A.: Temporal information extraction for question answering using syntactic dependencies in an LSTM-based architecture (2017)
Li, Z., Wang, J., Zhang, N., He, C., He, K.: A topic-oriented clustering approach for domain services. J. Comput. Res. Dev. 51(2), 408–419 (2014). https://doi.org/10.7544/issn1000-1239.2014.20120776
Cai, M., Zhang, W.Y., Zhang, K.: Manuhub: a semantic web system for ontology-based service management in distributed manufacturing environments. J. IEEE Trans. Syst. Man Cybern. Part A-Syst. Hum. 41(3), 574–582 (2011). https://doi.org/10.1109/tsmca.2010.2076395
Lin, J., Yu, H., Shen, Z., Miao, C.: Using goal net to model user stories in agile software development. In: 2014 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). IEEE (2014). https://doi.org/10.1109/snpd.2014.6888731
Platzer, C., Dustdar, S.: A vector space search engine for web services. In: European Conference on Web Services (2005). https://doi.org/10.1109/ecows.2005.5
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Jiang, B., Chen, Y., Wang, Y., Liu, P. (2019). Service Discovery Method for Agile Mashup Development. In: Sun, Y., Lu, T., Yu, Z., Fan, H., Gao, L. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2019. Communications in Computer and Information Science, vol 1042. Springer, Singapore. https://doi.org/10.1007/978-981-15-1377-0_3
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