@inproceedings{1abda9227b3a4b75b7d50720f16bc668,
title = "GSR: A Resource Model and Semantics-based API Recommendation Algorithm",
abstract = "With the rapid development of Web services, more and more Web services are published on the Internet. A Mashup application that aggregates multiple Web APIs is also becoming more popular. But it also brings a problem that is how to find a suitable API among a wide variety of APIs has become a challenge. To this end, this paper proposes a web service recommendation algorithm that combines graph databases and semantics. In this algorithm, we propose to use graph database to build a two-layer structure resource model. First, we use LDA for topic classification and classify Mashup and API of the same classification into the same category respectively. This helps reduce the number of searches for Mashup and API. When a user enters a requirement document, Word2vec and WMD algorithms are used to find similar Web API description text. Finally, we use similarity and API history invokes to propose a ranking algorithm to generate a recommendation list. Through real-world data, this experiment has a better-recommended performance.",
keywords = "API recommendation, LDA, Resource Model, Word Mover's Distance",
author = "Jiawei Wang and Guorong Cui and Xiaoke Zhu and Huijian Liu and Junsong Liu and Xuebin Jia",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 4th International Conference on Innovation in Artificial Intelligence, ICIAI 2020 ; Conference date: 08-05-2020 Through 11-05-2020",
year = "2020",
month = may,
day = "8",
doi = "10.1145/3390557.3394128",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "184--188",
booktitle = "Proceedings of the 2020 4th International Conference on Innovation in Artificial Intelligence, ICIAI 2020",
address = "美国",
}