Keyword Search Based Mashup Construction with Guaranteed Diversity

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Abstract

To assist system engineers in efficiently constructing mashups, the keyword search based approach is proposed recently, which finds the optimal mashup of services with respect to QoS. However, we claim that the diversity of mashups should be taken into account due to the ambiguity of input keywords, so that the returned diverse set of mashups can improve user satisfaction by covering various possible user demands behind the keywords. For that, we present a novel keyword search based service composition approach that finds the top-k mashups dissimilar to each other. Specifically, our approach firstly searches for specific subtrees that contain all given keywords in a service connection graph as candidate mashups, and then uses an efficient graph-based algorithm to select the final diverse top-k set without evaluating the similarity between each pair of mashups. We conduct the evaluations of our approach on a real world data set crawled from the ProgramableWeb.com. The experimental results demonstrate that our approach outperforms the previous work on two selected metrics.

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Cheng, H., Zhong, M., Wang, J., & Qian, T. (2019). Keyword Search Based Mashup Construction with Guaranteed Diversity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11707 LNCS, pp. 423–433). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-27618-8_31

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