机译:用5个W建模中文微博以提取主题标签
College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;
College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;
College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;
College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;
College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;
College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;
College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;
Twitter; Tagging; Semantics; Computational modeling; Algorithm design and analysis; Syntactics; Sentiment analysis;
机译:五W的主题链接标签抽取的中文微博建模。
机译:使用基于Hashtag图的主题模型连接语义相关的单词,而无需在微博中同时出现
机译:在微博环境中使用基于LDA的主题模型的个性化主题标签推荐方法
机译:基于5W模型的中文微博主题标签确定
机译:中国农业对气候变化适应动态建模的主题
机译:基于信息分类层次结构的地震应急响应的微博主题词检测模型
机译:用五个WS为主题标签提取建模中国微博
机译:2014年TREC上的pKUICsT微博跟踪:TTG的有效微博搜索和自适应聚类算法的特征提取。