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Abstract

The novelty of knowledge claims in a research paper can be considered an evaluation criterion for papers to supplement citations. To provide a foundation for research evaluation from the perspective of innovativeness, we propose an automatic approach for extracting innovative ideas from the abstracts of technology and engineering papers. The approach extracts N-grams as candidates based on part-of-speech tagging and determines whether they are novel by checking the Scopus® database to determine whether they had ever been presented previously. Moreover, we discussed the distributions of innovative ideas in different abstract structures. To improve the performance by excluding noisy N-grams, a list of stopwords and a list of research description characteristics were developed. We selected abstracts of articles published from 2011 to 2017 with the topic of semantic analysis as the experimental texts. Excluding noisy N-grams, considering the distribution of innovative ideas in abstracts, and suitably combining N-grams can effectively improve the performance of automatic innovative idea extraction. Unlike co-word and co-citation analysis, innovative-idea extraction aims to identify the differences in a paper from all previously published papers.

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Abstract

To more reasonably allocate a paper's credit, this article argues that both a paper's authors and references contribute to a given paper. Accordingly, we quantitatively represent the proportion of contributions from each author and reference to a paper. A paper's credit can be allocated among its authors and references based on their contributions. All papers carry innate credit because of publication. If cited, they also carry external credit from the citing papers. The proportion of a paper's credit allocated to references can be regarded as a credit output and serves as an input for these references. In this scenario, only the credit assigned to a paper's authors remains as the paper's deserved credit. The credit of papers can be transferred in a direction opposite that of knowledge diffusion. Via this method, the estimate of an individual reference's contribution incorporates content-based citation analysis, a promising method to differentiate different citations. A paper's deserved credit represents the contribution of the paper's authors to the scientific community via the new knowledge they provide in the paper. Therefore, it is rational to evaluate papers according to their deserved credit, not the credit they carry.