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Optimization of the subject directory in a government agriculture department web portal
Author(s) -
Zhang Jin,
Zhai Shanshan,
Stevenson Jennifer Ann,
Xia Lixin
Publication year - 2016
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23550
Subject(s) - directory , subject (documents) , computer science , government (linguistics) , subject matter expert , world wide web , psychology , artificial intelligence , linguistics , philosophy , expert system , operating system
We investigated a subject directory in the US A griculture D epartment‐ E conomic R esearch S ervice portal. Parent–child relationships, related connections among the categories, and related connections among the subcategories in the subject directory were optimized using social network analysis. The optimization results were assessed by both density analysis and edge strength analysis methods. In addition, the results were evaluated by domain experts. From this study, it is recommended that four subcategories be switched from their original four categories into two different categories as a result of the parent–child relationship optimization. It is also recommended that 132 subcategories be moved to 40 subcategories and that eight categories be moved to two categories as a result of the related connection optimization. The findings show that optimization boosted the densities of the optimized categories, and the recommended connections of both the related categories and subcategories were stronger than the existing connections of the related categories and subcategories. This paper provides visual displays of the optimization analysis as well as suggestions to enhance the subject directory of this portal.