CAJ | 학술논문

新闻话题的特征表示是建立话题模型以及进行话题聚类（融合）的基础，传统的特征构建一般采用关键字构成的向量表示模型，未对特征的选取、分类以及质量等方面进行完整的研究，因此本文拟针对互联网新闻文档进行特征提取、特征构建以及话题聚类质量分析等方面的系统研究，阐明话题特征的选择与构建对文本话题研究的影响，为后续的话题检测与追踪等应用提供更科学的特征理论模型。实验结果表明经过话题特征优选后的聚类效果有助于提高话题模型的准确性，避免噪声特征带来的话题歧义。
신문화제적특정표시시건립화제모형이급진행화제취류（융합）적기출，전통적특정구건일반채용관건자구성적향량표시모형，미대특정적선취、분류이급질량등방면진행완정적연구，인차본문의침대호련망신문문당진행특정제취、특정구건이급화제취류질량분석등방면적계통연구，천명화제특정적선택여구건대문본화제연구적영향，위후속적화제검측여추종등응용제공경과학적특정이론모형。실험결과표명경과화제특정우선후적취류효과유조우제고화제모형적준학성，피면조성특정대래적화제기의。
Feature representation for news topic is the foundation for modeling and clustering news topic. Traditional methods for features construction commonly use keywords to build a vector representation model taking no considera-tion of feature selection, feature classification as well as performance evaluation. Aiming at this issue, to provide more reasonable feature model for Topic Detection and Tracking (TDT), this paper intends to carry out a systematic study on feature selection, feature construction and performance evaluation for Internet news, and discusses how the feature se-lection and construction affect the study on texts topic. Experimental results show that the feature model selected and reconstructed by this paper improves the precision of topic clustering and effectively avoids the ambiguity by noise features.