文献类型：期刊文献

英文题名：Popularity-Aware and Diverse Web APIs Recommendation Based on Correlation Graph

作者：Wu, Shengqi[1];Shen, Shigen[2];Xu, Xiaolong[3];Chen, Ying[4];Zhou, Xiaokang[5,6];Liu, Dongning[7];Xue, Xiao[8];Qi, Lianyong[1,9]

机构：[1]Qufu Normal Univ, Sch Comp Sci, Jining 273165, Peoples R China;[2]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing 312010, Peoples R China;[3]Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 211544, Peoples R China;[4]Beijing Informat Sci & Technol Univ, Comp Sch, Beijing 100096, Peoples R China;[5]Shiga Univ, Fac Data Sci, Hikone 5228522, Japan;[6]RIKEN, Ctr Adv Intelligence Project, Tokyo, Japan;[7]Guangdong Univ Technol, Sch Comp Sci & Technol, Guangzhou 510006, Peoples R China;[8]Tianjin Univ, Coll Intelligence & Comp, Tianjin 300072, Peoples R China;[9]Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China

年份：0

外文期刊名：IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS

收录：SCI-EXPANDED(收录号：WOS:000791713500001)、、EI(收录号：20221912092522)、Scopus(收录号：2-s2.0-85129588640)、WOS

基金：This work was supported in part by the National Science Foundation of China under Grant 61872219 and Grant 62177014; in part by the Natural Science Foundation of Shandong Province under Grant ZR2019MF001; in part by the Open Foundation of the State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, under Grant SKLNST-20201-06; in part by the Natural Science Foundation of China under Grant 62177014; and in part by the Research Foundation of Hunan Provincial Education Department of China under Grant 20B222.

语种：英文

外文关键词：Mashups; Correlation; Steiner trees; Software; Computer science; Telecommunications; Switches; Application programming interface (API) compositions; diversity; popularity; recommendation

外文摘要：The ever-increasing web application programming interfaces (APIs) in various service-sharing communities (e.g., ProgrammableWeb.com and Mashape.com) have enabled software developers to quickly create their interested mashups conveniently and economically. However, the big volume of candidate web APIs and their differences often make it hard for software developers to discover a set of appropriate web APIs for mashup creation by considering API functions and API quality performances (e.g., popularity, compatibility, and diversity) simultaneously. These decrease the mashup development success rate and the mashup developers' satisfaction significantly. In view of these challenges, a novel web APIs' recommendation method named the popularity-aware and diverse method of web API compositions' recommendation (PD-WACR) is proposed in this article. In concrete, we model web APIs' functions, popularity, and compatibility with an API correlation graph. Afterward, correlation graph-based web APIs' recommendation is performed with popularity and compatibility guarantee. Moreover, a top-k strategy is adopted in the recommendation process, so as to diversify the final recommended web APIs' results. Finally, massive experiments are carried out on a real-world web API dataset crawled from ProgrammeableWeb.com. Experimental comparisons with related methods show the advantages and innovations of the proposed PD-WACR method.