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Social Network Analysis and Mining
Published in: Social Network Analysis and Mining 1/2018

01-12-2018 | Original Article

An optimal method for URL design of webpage journals

Authors: Zahra Mousavilou, Rozita Jamili Oskouei

Published in: Social Network Analysis and Mining | Issue 1/2018

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Abstract

In spite of a large number of accessible conference or online research papers conducted by various researchers, their URL structures lack content-related information. This has made the search of studies in a certain field difficult. Note that a webpage URL is not merely an address to reach the content in Internet. The importance of information in a URL structure becomes more apparent when the optimal URL structure design and the use of keywords in URL are emphasized in search engine optimization. In this study, a mode is offered to optimize the URL structure of webpage journals. The related URL becomes more readable by determining the journal titles and inserting this title in the URL related to the pages containing abstracts. Therefore, researchers can easily find the articles. The proposed model was tested on 1300 articles in 160 journals including Elsevier, Springer, IEEE, and Willie’s Online Library using artificial intelligence. The results are acceptable using F-measure evaluation criteria.
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Metadata
Title
An optimal method for URL design of webpage journals
Authors
Zahra Mousavilou
Rozita Jamili Oskouei
Publication date
01-12-2018
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2018
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-018-0532-z

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