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

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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10.1145/3477495.3531962

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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
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 07 July 2022

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    Author Tags

    1. apis recommendation
    2. compatibility
    3. correlation graph of apis
    4. diversity

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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
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    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    • (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
    • (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
    • (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
    • (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
    • (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
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    • (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
    • (2024)Cooperative Mashup Embedding Leveraging Knowledge Graph for Web API RecommendationIEEE Access10.1109/ACCESS.2024.338448712(49708-49719)Online publication date: 2024
    • (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
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