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164 Journal of Library Science in China, Vol.10, 2018

scale and reasoning with some purpose. It has obvious advantages in understanding and processing
unstructured text. Cognitive computing is mainly used to solve problems with ambiguity and
uncertainty. The introduction of cognitive computing into the evaluation field of academic papers
is expected to solve both subjectivity and inefficiency in qualitative evaluation, as well as the lack
of analyzing content in quantitative evaluation. Through the relevant document surveys, this paper
discusses the research and practice of cognitive computing, analyzes the development process of
academic paper evaluation, and discusses the development bottleneck that the current evaluation
methods face with and evaluation essence. Mainly, this paper focuses on the new perspective
based on cognitive calculation to evaluate academic papers, and we analyze the realization path
of cognitive computing in the evaluation of academic papers and key issues in constructing a
cognitive computing system for academic papers.
It is found that the development of academic paper evaluation is closely related to the changes in
the way of scientific communication. The essence of academic paper evaluation is the evaluation
of its academic value. Social value and economic value are the results of the application of
academic value in different fields. The academic value and quality of an academic paper depend
on its originality. From the perspective of semantic content, combing the multisource data sets
and related knowledge base to construct the academic evaluation system based on the cognitive
computing is expected to become one of the most important development directions of the
evaluation of academic papers in the future.
The cognitive computing system proposed in this paper is a new idea for the evaluation
of academic papers, and makes full use of the current advanced technology and big data
thinking, which is of great value to optimize the existing evaluation theory and practice of
academic papers. Firstly, the cognitive computing system of academic papers takes into
account the multiple features including paper content, reference and citing papers, to realize the
perfect combination of peer review and bibliometrics, and can make up its respective defects
simultaneously. Secondly, the evaluation of academic papers based on cognitive computing is
helpful in the fields of research management, discipline construction, reviews by editor and
expert, and user’s literature acquisition and reading experience et al. However, we are still in the
early stage of cognitive system development, and there are several challenges to apply cognitive
computing to academic paper evaluation. Among them, the datamation and semantization of the
academic papers, and the machine learning model for the evaluation of academic papers are the
two key issues that need to be solved in the construction of the cognitive computing system for
academic papers.