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Information 2018, 9(9), 227; https://doi.org/10.3390/info9090227

Feature Selection and Recognition Methods for Discovering Physiological and Bioinformatics RESTful Services

1
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2
Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, Beijing 100083, China
3
Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Received: 26 July 2018 / Revised: 24 August 2018 / Accepted: 28 August 2018 / Published: 6 September 2018
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Abstract

Many physiology and bioinformatics research institutions and websites have opened their own data analysis services and other related Web services. It is therefore very important to be able to quickly and effectively select and extract features from the Web service pages to learn about and use these services. This facilitates the automatic discovery and recognition of Representational State Transfer or RESTful services. However, this task is still challenging. Following the description feature pattern of a RESTful service, the authors proposed a Feature Pattern Search and Replace (FPSR) method. First, they applied a regular expression to perform a matching lookup. Then, a custom string was used to substitute the relevant feature pattern to avoid the segmentation of its feature pattern and the loss of its feature information during the segmentation process. Experimental results showed in the visualization that FPSR obtained a clearer and more obvious boundary with fewer overlaps than the test without using FPSR, thereby enabling a higher accuracy rate. Therefore, FPSR allowed the authors to extract RESTful service page feature information and achieve better classification results. View Full-Text
Keywords: RESTful services; feature extraction; web page classification; service discovery RESTful services; feature extraction; web page classification; service discovery
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Song, C.; Gao, X.; Wang, Y.; Li, J.; Fan, L.; Qin, X.; Zhou, Q.; Wang, Z.; Huang, L. Feature Selection and Recognition Methods for Discovering Physiological and Bioinformatics RESTful Services. Information 2018, 9, 227.

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