Paper Info
Title
Mining Collaboration Patterns Between Apis For Mashup Creation In Web Of Things
Abstract
The Web of Things (WoT) extends the concept of "Internet of Things (IoT)'' in that smart devices in the physical world can be interacted with or integrated via popular web technologies (e.g., HTML, HTTP, and Web API). With the WoT, smart devices can use Web APIs to make their data or functionalities accessible by software. With the popularization of Web 2.0 Mashup applications, creating Mashup applications for the IoT (or WoT) via combining different APIs, also has aroused increasing interests. This paper proposes an approach to mining collaboration patterns between APIs to aid mashup creation for the WoT. The goal of the approach is to disclose what kinds of Web APIs are frequently combined together in mashup creation and what kinds of API combination are popular. Based on a real-world mashup and Web API repository, Pragrammable Web. com, we exploit the text description and tags of Web APIs and employ an FP-growth-based association mining algorithm to discover popular collaboration patterns between APIs. To overcome the deficiency caused by tag sparsity, the approach also develops a method based on TF/IDF to expand the tags of Web APIs. The experimental results validated the performance of the proposed approach.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2894297
IEEE ACCESS
Keywords
Field
DocType
Web API, collaboration patterns, association rule mining, web of things, mashup, tag expansion
Mashup,World Wide Web,Web of Things,Computer science,Computer network
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Mingdong Tang194.06
Yanmin Xia200.68
Bing Tang3314.55
Yongmei Zhou471.44
Buqing Cao520023.96
Rong Hu62111.79