本文選題：辯論 + 爭議節(jié)點��； 參考：《電子科技大學學報》2017年02期

【摘要】：微博內容具有信息混雜和不確定性等特點,傳統(tǒng)可信度判別方法存在一定局限性。因此,該文提出一種面向微博可信度評估的辯論有向圖模型,從辯論的角度出發(fā),以圖模型直觀、形象化地描述了辯論推演過程。通過話題語料構成爭議節(jié)點,利用爭議間的主題情感和潛在邏輯關系定義規(guī)則可信度,并設置圖中邊的權值來代表爭議間的防衛(wèi)和攻擊強度。根據(jù)相關算法得出結論的可信度,遞歸進行辯論圖演化,得到需判別信息的可信度。實驗結果表明該模型比傳統(tǒng)方法綜合指標值平均提升6%。
[Abstract]:The content of Weibo is characterized by mixed information and uncertainty, and there are some limitations in the traditional method of credibility judgment. Therefore, this paper presents a debate directed graph model for Weibo credibility evaluation. From the point of view of debate, the process of debate deduction is described visually and visually by the graph model. The topic corpus is used to form the dispute node, the subject emotion and the underlying logic relationship between the disputes are used to define the rule credibility, and the weights of the edges in the graph are set to represent the defense and attack intensity between the disputes. The credibility of the conclusion is obtained according to the correlation algorithm, and the credibility of the discriminant information is obtained by recursive evolution of the argument graph. The experimental results show that the synthetic index value of this model is 6 times higher than that of the traditional method.
【作者單位】： 昆明理工大學信息工程與自動化學院;云南省計算機技術應用重點實驗室;昆明理工大學教育技術與網(wǎng)絡中心;
【基金】：國家自然科學基金(81360230,81560296,61462056,61462051)
【分類號】：TP391.1;TP393.092
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本文編號：1889805