CAJ | 학술논문

随着网络上发布的Web API服务越来越多，如何推荐给开发者用户感兴趣、信誉度高的Web API服务，以构建高质量高可信的软件服务系统，成为一个具有挑战性的研究问题。为此，提出一种基于用户使用历史与信誉评价的Web API服务推荐方法。计算用户使用历史记录与Web API之间的相似度，获得Web API的用户兴趣值。综合用户的Web API评分，调用Web API的Mashup服务的评价贡献和Alexa统计的Web API访问流量，获得Web API的信誉评价值。根据Web API的用户兴趣值以及信誉评价值，实现Web API的排名与推荐。实验结果表明，该方法推荐的Web API用户兴趣度DCG值高于SR-Based方法，服务信誉度DCG值高于UI-Based方法。
수착망락상발포적Web API복무월래월다，여하추천급개발자용호감흥취、신예도고적Web API복무，이구건고질량고가신적연건복무계통，성위일개구유도전성적연구문제。위차，제출일충기우용호사용역사여신예평개적Web API복무추천방법。계산용호사용역사기록여Web API지간적상사도，획득Web API적용호흥취치。종합용호적Web API평분，조용Web API적Mashup복무적평개공헌화Alexa통계적Web API방문류량，획득Web API적신예평개치。근거Web API적용호흥취치이급신예평개치，실현Web API적배명여추천。실험결과표명，해방법추천적Web API용호흥취도DCG치고우SR-Based방법，복무신예도DCG치고우UI-Based방법。
With the release of more and more Web API services on Internet,it becomes a challenging research problem that how to recommend Web APIs that developer user are interested in and reputation degrees are high,to construct high quality and trustworthy software service system. This paper presents Web API service recommendation approach based on user usage history and reputation evaluation ( WASR) . It computes the similarity between user history records and Web API services,and gets user interest degree. Service reputation degree is computed by considering the user score of Web API,the score contributions of those Mashup services calling the Web API, and traffic flow of Web API based on statistical data by Alexa. It ranks and recommends Web API services according to the user interest degree and service reputation degree of Web APIs. Experimental results show that this approach can recommend Web API services with higher DCG of user interest degree than those of SR-based approach,and higher DCG of service reputation degree than those of UI-based approach.