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A connectivity based recommendation approach for data service mashups

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Abstract

Data service mashup provides a development fashion that integrates heterogeneous data from multiple data sources into a single Web application. This paper focuses on the problem of recommending useful suggestions for developing data service mashups based on the association relationship of data services. Firstly the data service association relationship is analyzed from three angles: the data dependence, inheritance and the potential association between data services. Based on the analysis, a measure of the data service association relationship called connectivity is proposed to assess the relationship of any two data services. Then a recommendation method is proposed to suggest the next useful data services based on the connectivity. The experimental evaluation demonstrates the utility of our method.

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APA

Zhang, S., Wang, G., Zhang, Z., & Han, Y. (2015). A connectivity based recommendation approach for data service mashups. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9051, pp. 133–147). Springer Verlag. https://doi.org/10.1007/978-3-319-20370-6_11

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