[目的]对国内外语义新颖性研究相关进展进行归纳整理,总结相关技术,为后续研究提供参考.[文献范围]利用"novelty of the literature""semantic novelty""文献新颖性"等关键词及"语义新颖性and文献评价"等检索式在Web of Science、Elsevier、Springer、谷歌学术及中国知网、万方、维普等数据库中进行文献检索,经过阅读整理并对具有代表性的相关理论进行溯源,最终筛选出70篇文献进行评述.[方法]对国内外语义新颖性相关研究进行梳理,围绕新颖性定义、新颖性评价指标和不同评价方法等分析科技文献语义新颖性评价的发展现状及未来趋势.[结果]语义新颖性评价逐渐受到学界的广泛关注,已有相关研究对语义内容进行挖掘评价,但尚未形成统一的度量指标.[局限]现有的文献新颖性多从外部特征进行评价,直接以语义新颖性为主题的研究文献数量较少,在支撑综述方面存在局限性.[结论]科技文献的语义新颖性评价根本在于语义内容的新颖性,定量研究已成为主流研究方法,但评价指标的计算方式尚需明确,未来的新颖性评价发展方向应结合定性与定量方法全面分析,实现科学、合理的综合学术评价.
Reviewing Research on Semantic Novelty in Sci-Tech Literature
[Objective]This paper reviews the research progress on semantic novelty in China and abroad.It explores relevant techniques and provides references for future studies.[Coverage]We used keywords such as"novelty of the literature","semantic novelty","literature novelty",and search expressions like"semantic novelty and literature evaluation"to retrieve literature from Web of Science,Elsevier,Springer,Google Scholar,as well as Chinese databases like CNKI,Wanfang,and VIP.A total of 70 representative literature were selected for review.[Methods]We summarized research on semantic novelty,focusing on the definition of novelty,evaluation indicators,and different evaluation methods.We also discussed the current development status and future trends of evaluating semantic novelty in scientific literature.[Results]Semantic novelty evaluation has gradually received widespread attention from the academic community.Related studies have evaluated semantic content without establishing a unified measurement index.[Limitations]Existing evaluation of literature novelty mainly focuses on external features.Fewer research papers directly addressed semantic novelty,limiting support for reviews.[Conclusions]The evaluation of semantic novelty in scientific literature fundamentally lies in the novelty of semantic content.Quantitative research has become the mainstream method,but the calculation method of evaluation indicators needs to be clarified.Future studies on novelty evaluation should combine qualitative and quantitative methods for more comprehensive evaluations.
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万方数据
