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DINRec: Deep Interest Network Based API Recommendation Approach for Mashup Creation

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Web Information Systems Engineering – WISE 2019 (WISE 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11881))

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Abstract

Recommending appropriate APIs for Mashup creation has become a challenge as the number of APIs from different sources grows fast. In order to understand the relationships among multiple ecosystem APIs, most existing API recommendation methods focus on semantic similarity relationships but underutilize the composition and cooperation relationships between APIs, which may lead to low recommendation precision. In view of this problem, a Deep Interest Network based API Recommendation approach (DINRec) for Mashup development is proposed in this paper. In this approach, APIs are chosen incrementally for compositing into a Mashup and in that process the embedding vector of the Mashup’s existing composition features will be updated adaptively by using Deep Interest Network. Moreover, a Doc2simu model is used to help training industrial deep networks with relatively small amounts of dataset. Finally, some experiments on real-world dataset are implemented to verify the efficiency of our proposed approach.

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Acknowledgment

This work was supported in part by the National Natural Science Foundation of China under Grant 61572187, Grant 61872139, Grant 61772193 and Grant 61702181, in part by the Natural Science Foundation of Hunan Province under Grant 2017JJ2098, Grant 2018JJ2136, Grant 2018JJ3190 and Grant 2018JJ2139, and in part by the Educational Commission of Hunan Province of China under Grant 17C0642.

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Authors and Affiliations

  1. Key Laboratory of Knowledge Processing and Networked Manufacturing, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Yong Xiao, Jianxun Liu, Rong Hu, Buqing Cao & Yingcheng Cao

  2. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Yong Xiao, Jianxun Liu, Rong Hu, Buqing Cao & Yingcheng Cao

Authors
  1. Yong Xiao
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  2. Jianxun Liu
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  3. Rong Hu
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  4. Buqing Cao
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  5. Yingcheng Cao
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Corresponding author

Correspondence to Jianxun Liu .

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Editors and Affiliations

  1. University of Hong Kong, Hong Kong SAR, China

    Reynold Cheng

  2. University of Ioannina, Ioannina, Greece

    Nikos Mamoulis

  3. University of California, Los Angeles, CA, USA

    Yizhou Sun

  4. Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China

    Xin Huang

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Xiao, Y., Liu, J., Hu, R., Cao, B., Cao, Y. (2019). DINRec: Deep Interest Network Based API Recommendation Approach for Mashup Creation. In: Cheng, R., Mamoulis, N., Sun, Y., Huang, X. (eds) Web Information Systems Engineering – WISE 2019. WISE 2020. Lecture Notes in Computer Science(), vol 11881. Springer, Cham. https://doi.org/10.1007/978-3-030-34223-4_12

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  • DOI: https://doi.org/10.1007/978-3-030-34223-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34222-7

  • Online ISBN: 978-3-030-34223-4

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