摘要
【目的】充分挖掘科学知识网络社群多元特征,提升领域新兴趋势预测效果。【方法】基于e-Health领域新兴社群到热点社群的成长路径回溯,本文提出一种融合词汇功能属性的新兴趋势多元特征预测模型。【结果】在e-Health领域,所融合的主题、技术等词汇功能属性特征能够提升新兴趋势预测性能,综合结构、影响、序列和属性4组特征的RF算法模型效果最佳。词汇功能属性规模大、密度低、中介中心性高、波动率大的社群更有可能成为新兴社群。序列特征对新兴社群预测效果欠佳,可能受到新兴社群的前瞻性影响。【局限】词汇功能识别结果存在一定领域依赖,结论扩展到其他领域的有效性需进一步验证。【结论】充分挖掘科学文本词汇细粒度语义特征,能够有效提升新兴趋势预测性能,对科学内容评价和科技决策支持具有一定参考意义。
[Objective]This paper explores the diverse characteristics of knowledge network communities to enhance the predicting effectiveness of emerging scientific trends.[Methods]Based on the retrospective growth path of e-Health communities,we proposed a model integrating vocabulary functional attributes to predict emerging trends with diverse features.[Results]In the e-Health field,integrating topic,technical,and other vocabulary functional attribute features can improve the prediction performance of emerging trends.The RF algorithm model,which combines structure,influence,sequence,and attribute features,performed the best.Communities with large vocabulary functional attribute scales,low density,high mediated centrality,and high volatility were more likely to become emerging communities.Sequence features have limited effectiveness in predicting emerging communities,possibly due to the forward-looking impact of emerging communities.[Limitations]The identification results of vocabulary functionality are domain-dependent,and the validity of the conclusions extended to other fields needs further verification.[Conclusions]Fully exploring the fine-grained semantic features of scientific vocabulary can effectively enhance the prediction performance of emerging trends.It provides valuable insights for scientific content evaluation and technology decision support.
作者
操玉杰
向荣荣
毛进
袁丹妮
Cao Yujie;Xiang Rongrong;Mao Jin;Yuan Danni(School of Information Management,Central China Normal University,Wuhan 430079,China;School of Information Management,Wuhan University,Wuhan 430072,China)
出处
《数据分析与知识发现》
EI
CSCD
北大核心
2024年第4期99-111,共13页
Data Analysis and Knowledge Discovery
基金
国家社会科学基金项目(项目编号:20CTQ024)研究成果之一
关键词
新兴趋势
词汇功能
社群预测
机器学习
Emerging Trend
Lexical Function
Community Prediction
Machine Learning
