research-article

DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph

Authors:

Lianyong QiAuthors Info & Claims

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 395 - 404

https://doi.org/10.1145/3477495.3531962

Published: 07 July 2022 Publication History

Abstract

With the ever-increasing popularity of microservice architecture, a considerable number of enterprises or organizations have encapsulated their complex business services into various lightweight functions as published them accessible APIs (Application Programming Interfaces). Through keyword search, a software developer could select a set of APIs from a massive number of candidates to implement the functions of a complex mashup, which reduces the development cost significantly. However, traditional keyword search methods for APIs often suffer from several critical issues such as functional compatibility and limited diversity in search results, which may lead to mashup creation failures and lower development productivity. To deal with these challenges, this paper designs DAWAR, a diversity-aware Web APIs recommendation approach that finds diversified and compatible APIs for mashup creation. Specifically, the APIs recommendation problem for mashup creating is modelled as a graph search problem that aims to find the minimal group Steiner trees in a correlation graph of APIs. DAWAR innovatively employs the determinantal point processes to diversify the recommended results. Empirical evaluation is performed on commonly-used real-world datasets, and the statistic results show that DAWAR is able to achieve significant improvements in terms of recommendation diversity, accuracy, and compatibility.

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Cited By

Yan CZhong WZhai DKhan AGong WXu YXin B(2024)Popularity Bias in Correlation Graph-based API Recommendation for Mashup CreationACM Transactions on Intelligent Systems and Technology10.1145/365444516:1(1-18)Online publication date: 26-Dec-2024
https://dl.acm.org/doi/10.1145/3654445
Zhu MGu HChe XChen JZhao QLiu FZheng Y(2024)A Novel Diversified API Recommendation for Power System Sensors2024 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics62450.2024.00027(17-22)Online publication date: 19-Aug-2024
https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics62450.2024.00027
Li BQuan HWang JLiu PCai HMiao YYang YLi L(2024)Neural Library Recommendation by Embedding Project-Library Knowledge GraphIEEE Transactions on Software Engineering10.1109/TSE.2024.339350450:6(1620-1638)Online publication date: Jun-2024
https://doi.org/10.1109/TSE.2024.3393504
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Index Terms

DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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cover image ACM Conferences

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2022

3569 pages

ISBN:9781450387323

DOI:10.1145/3477495

General Chairs:
Enrique Amigo
UNED
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UAM and Amazon
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Julio Gonzalo
UNED
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Program Chairs:
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Spotify
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J. Shane Culpepper
RMIT University
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Gabriella Kazai
Waseda University

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Published: 07 July 2022

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the ARC DECRA
the National Natural Science Foundation of China
the Open Project of State Key Laboratory for Novel Software Technology
the Natural Science Foundation of Shandong Province

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SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 11 - 15, 2022

Madrid, Spain

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Cited By

Yan CZhong WZhai DKhan AGong WXu YXin B(2024)Popularity Bias in Correlation Graph-based API Recommendation for Mashup CreationACM Transactions on Intelligent Systems and Technology10.1145/365444516:1(1-18)Online publication date: 26-Dec-2024
https://dl.acm.org/doi/10.1145/3654445
Zhu MGu HChe XChen JZhao QLiu FZheng Y(2024)A Novel Diversified API Recommendation for Power System Sensors2024 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics62450.2024.00027(17-22)Online publication date: 19-Aug-2024
https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics62450.2024.00027
Li BQuan HWang JLiu PCai HMiao YYang YLi L(2024)Neural Library Recommendation by Embedding Project-Library Knowledge GraphIEEE Transactions on Software Engineering10.1109/TSE.2024.339350450:6(1620-1638)Online publication date: Jun-2024
https://doi.org/10.1109/TSE.2024.3393504
Wang XXi MLi YPan XWu YDeng SYin J(2024)SEHGN: Semantic-Enhanced Heterogeneous Graph Network for Web API RecommendationIEEE Transactions on Services Computing10.1109/TSC.2024.341732317:5(2836-2849)Online publication date: Sep-2024
https://doi.org/10.1109/TSC.2024.3417323
Wu HZhang YMa CLyu FHe BMitra BLiu X(2024)Result Diversification in Search and Recommendation: A SurveyIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.338226236:10(5354-5373)Online publication date: Oct-2024
https://doi.org/10.1109/TKDE.2024.3382262
Sun YWang XXu HWang Z(2024)MCBA: A Matroid Constraint-Based Approach for Composite Service Recommendation Considering Compatibility and Diversity : (Invited Paper)2024 IEEE International Conference on Service-Oriented System Engineering (SOSE)10.1109/SOSE62363.2024.00016(80-91)Online publication date: 15-Jul-2024
https://doi.org/10.1109/SOSE62363.2024.00016
Gu YCao JQian SZhu NGuan W(2024)ProSwats: A Proxy-based Scientific Workflow Retrieval Approach by Bridging the Gap between Textual and Structural Semantics2024 IEEE International Conference on Web Services (ICWS)10.1109/ICWS62655.2024.00111(932-943)Online publication date: 7-Jul-2024
https://doi.org/10.1109/ICWS62655.2024.00111
Hu X(2024)Biased Random Walk based Web API Recommendation in Heterogeneous Network2024 IEEE International Conference on Web Services (ICWS)10.1109/ICWS62655.2024.00038(172-177)Online publication date: 7-Jul-2024
https://doi.org/10.1109/ICWS62655.2024.00038
Zhang CQin SWu HZhang L(2024)Cooperative Mashup Embedding Leveraging Knowledge Graph for Web API RecommendationIEEE Access10.1109/ACCESS.2024.338448712(49708-49719)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3384487
Tang MXie FLian SMai JLi S(2024)Mashup-oriented API recommendation via pre-trained heterogeneous information networksInformation and Software Technology10.1016/j.infsof.2024.107428169:COnline publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.infsof.2024.107428
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