Abstract
A standard system, which is a powerful tool in maintaining the normal operations and development of a specific industry, is intrinsically a complex network composed of numerous standards which coordinate and interact with each other. In a networked standard system, the identification of critical standards is of great significance when drafting and revising standards. However, a majority of the existing literature has focused on the citation relationships between standards while ignoring the intrinsic interdependent relationships between the contents of standards. To overcome this limitation, we utilize the text similarity approach (TSA) to quantify the relationship intensity between each pair of standards, in order to generate a directed weighted network. The critical contribution of this study is that the similarity computed by the TSA is incorporated into the traditional PageRank algorithm for the identification of critical standards. The improved algorithm comprehensively considers the quantity and importance of neighboring standards and the citation intensity, as quantified by TSA. The algorithm is finally validated using the Chinese environmental health standards through comparison with the traditional PageRank algorithm and different classic measurements.
Highlights
Standards refer to the normative documents formulated by consensus and issued by recognized institutions, in order to achieve the best operations within a certain scope
Standards often play a synergistic role in the form of a standard system, which refers to an organic whole composed of numerous standards that interact and coordinate with each other. e specific manifestation of interaction and coordination is the citation between standards, which maps the transmission of information and knowledge carried by standard documents
Extensive literature in the field of network analysis has been devoted to the concept of centrality, which aims at answering a fundamental question: which nodes occupy the core positions of a network? Some centrality measurements have been proposed to evaluate the importance of nodes [48,49,50,51]
Summary
Standards refer to the normative documents formulated by consensus and issued by recognized institutions, in order to achieve the best operations within a certain scope. Wei et al [11] proposed an integrated multi-criteria decision-making method, which combined the entropy weight (EW) method and a TOPSIS method based on traditional node measurements, such as degree centrality and betweenness centrality Their existing research focused on simple 0-1 citation relationships, while ignoring the magnitude information of the relationships between pairs of standards, which can be reflected by their connections in terms of document contents. Text mining has provided fruitful algorithms for quantifying the similarity between different kinds of documents, which motived us to use TSA for the identification of critical standards in standard networks
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