CAJ | 학술논문

已有的微博用户相似性度量主要依据用户关系，实际上，在微博网络中，用户的标签信息直接表征了用户的兴趣爱好，是影响微博用户相似度的另一因素，为此，在网页相似度计算的基础上提出了融合用户关系和标签的微博用户相似性度量方法，该方法分别计算用户的链入标签相似度和链出标签相似度，并将其进行线性调和。实验从新浪微博采集实验数据，实验结果表明新方法对微博用户分类的准确率明显高于仅考虑用户关系的微博用户相似性计算方法。
이유적미박용호상사성도량주요의거용호관계，실제상，재미박망락중，용호적표첨신식직접표정료용호적흥취애호，시영향미박용호상사도적령일인소，위차，재망혈상사도계산적기출상제출료융합용호관계화표첨적미박용호상사성도량방법，해방법분별계산용호적련입표첨상사도화련출표첨상사도，병장기진행선성조화。실험종신랑미박채집실험수거，실험결과표명신방법대미박용호분류적준학솔명현고우부고필용호관계적미박용호상사성계산방법。
Existing measurement methods of micro-blogging usersˊsimilarity are mainly based on user relationships. In fact, user tags can directly characterize userˊs interests, and is another impacting factor of user similarity. A new similarity measurement method of micro-blogging users based on webpage similarity computation is given, which effectively integrates user relationships and tags. The new method firstly computes the similarity of link-into tags and link-out tags, and then obtaines the final similarity by liner meditating the two. The experiment result based on data collected from Sina Weibo indicates that the classification accuracy of the new method is obviously higher than the method that only considers user relationships.