CAJ | 학술논문

微博中隐含着舆论热点等与特定话题相关的有价值的信息。因此，针对微博数据分析（如话题发现等）的工作成了当前的研究热点。由于微博内容和形式的高度自由，使得相关的研究工作面临着垃圾数据噪声大、有用数据提取难的问题。然而，目前针对非公共话题的中文垃圾微博过滤尚无有效方法。提出一种基于多视角特征融合的垃圾微博过滤方法。该方法首先从微博的结构和内容两个视角建立规则，再与微博文本分词结果进行融合构造复合特征，并以此对垃圾微博进行过滤。通过在真实数据集上的实验表明多视角融合的特征使得过滤效果有明显提升。
미박중은함착여론열점등여특정화제상관적유개치적신식。인차，침대미박수거분석（여화제발현등）적공작성료당전적연구열점。유우미박내용화형식적고도자유，사득상관적연구공작면림착랄급수거조성대、유용수거제취난적문제。연이，목전침대비공공화제적중문랄급미박과려상무유효방법。제출일충기우다시각특정융합적랄급미박과려방법。해방법수선종미박적결구화내용량개시각건립규칙，재여미박문본분사결과진행융합구조복합특정，병이차대랄급미박진행과려。통과재진실수거집상적실험표명다시각융합적특정사득과려효과유명현제승。
As microblog contains valuable information, data analysis on microblog such as topic detection has become a research hotspot.Due to the high flexibility of microblog′s content and form, noisy data is a big challenge for microblog analysis.Therefore, no effective method has been developed for non-public topic Chinese spam microblog filtering until now.To fill this gap, a new method was proposed to fuse multi-angle features extracted from both the content and struc-ture of microblog.The fused features were then employed for filtering spam microblog with classifiers.Experiments on real data demonstrate that the fusion of multi-angle features can effectively improve the performance of spam filtering.