Abstract
In this paper we propose a multi-layered model meant for the selection of data services for web application design. Our aim is at complementing existing data service selection criteria, e.g., matching based on (semantic) data coming from the services, by also considering the experience of other developers, who used the services in the past for designing their own web applications. In this sense, it becomes crucial the importance that a developer gives to past experiences of other developers in selecting a data service, that might depend on the social relationships that relate the developers each other as well. The model proposed in this paper takes into account these challenging issues by considering available data services, web applications where services have been aggregated, and social relationships between web application developers, which identify different kinds of social patterns.
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References
Li, Y., Wang, Y., Du, J.: E-FFC: an enhanced form-focused crawler for domain-specific Deep Web databases. J. of Intelligent Information Systems 40(1), 159–184 (2013)
Quarteroni, S., Brambilla, M., Ceri, S.: A Bottom-up, Knowledge-Aware Approach to Integrating and Querying Web Data Services. ACM Trans. on the Web 7(4), 44–76 (2013)
Bozzon, A., Brambilla, M., Ceri, S., Mazza, D.: Exploratory Search Framework for Web Data Services. VLDB Journal 22, 641–663 (2013)
Bianchini, D., De Antonellis, V., Melchiori, M.: QoS in ontology-based service classification and discovery. In: 15th International Workshop on Database and Expert Systems Applications, pp. 145–150. IEEE Computer Society, Los Alamitos (2004)
Dillon, S., Stahl, F., Vossen, G.: Towards the web in your pocket: Curated data as a service. In: Nguyen, N.T., Trawinski, B., Katarzyniak, R., Jo, G.S. (eds.) Advanced Methods for Computing Collective Intelligence, pp. 25–34. Springer, Berlin Heidelberg (2013)
Balakrishnan, R., Kambhampati, S., Manishkumar, J.: Assessing Relevance and Trust of the Deep Web Sources and Results Based on Inter-Source Agreement. ACM Trans. on the Web 7(2), 32 (2013)
Al-Sharawneh, J., Williams, M., Wang, X., Goldbaum, D.: Mitigating risk in web-based social network service selection: follow the leader. In: 6th Int. Conference on Internet and Web Applications and Services, pp. 156–164. IARIA XPS Press (2011)
Malik, Z., Bouguettaya, A.: RATEWeb: Reputation Assessment for Trust Establishment among Web Services. VLBD Journal 18, 885–911 (2009)
Bianchini, D., De Antonellis, V., Melchiori, M.: Capitalizing the designers’ experience for improving web API selection. In: Meersman, R., Panetto, H., Dillon, T., Missikoff, M., Liu, L., Pastor, O., Cuzzocrea, A., Sellis, T. (eds.) OTM 2014. LNCS, vol. 8841, pp. 364–381. Springer, Heidelberg (2014)
Fuxman, A., Giorgini, P., Kolp, M., Mylopoulos, J.: Information systems as social structures. In: 2nd Int. Conf. on Formal Ontologies for Information Systems, pp. 12–21. ACM, New York (2001)
Gupta, V., Lehal, G.: A Survey of Text Mining Techniques and Applications. J. of Emerging Technologies in Web Intelligence 1(1), 60–76 (2009)
Bianchini, D., De Antonellis, V., Melchiori, M.: Semantic collaborative tagging for web APIs sharing and reuse. In: Brambilla, M., Tokuda, T., Tolksdorf, R. (eds.) ICWE 2012. LNCS, vol. 7387, pp. 76–90. Springer, Heidelberg (2012)
dos Santos, T., de Araujo, R., Magdaleno, A.: Identifying Collaboration Patterns in Software Development Social Networks. J. of Computer Science, 51–60 (2010)
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Bianchini, D., De Antonellis, V., Melchiori, M. (2015). Leveraging Social Patterns in Web Application Design. In: Cimiano, P., Frasincar, F., Houben, GJ., Schwabe, D. (eds) Engineering the Web in the Big Data Era. ICWE 2015. Lecture Notes in Computer Science(), vol 9114. Springer, Cham. https://doi.org/10.1007/978-3-319-19890-3_2
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DOI: https://doi.org/10.1007/978-3-319-19890-3_2
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