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DFKI-DKT at SemEval-2017 Task 8: Rumour Detection and Classification using Cascading Heuristics

机译:DFKI-DKT在SemEval-2017上的任务8:使用级联启发式算法进行谣言检测和分类

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We describe our submissions for SemEval-2017 Task 8, Determining Rumour Veracity and Support for Rumours. The Digital Curation Technologies (DKT) (Rehm and Sasaki, 2016, 2015) team at the German Research Center for Artificial Intelligence (DFKI) participated in two subtasks: Subtask A (determining the stance of a message) and Subtask B (determining veracity of a message, closed variant). In both cases, our implementation consisted of a Multivariate Logistic Regression (Maximum Entropy) classifier coupled with hand-written patterns and rules (heuristics) applied in a post-process cascading fashion. We provide a detailed analysis of the system performance and report on variants of our systems that were not part of the official submission.
机译:我们将介绍SemEval-2017任务8(确定谣言的准确性和对谣言的支持)的提交内容。德国人工智能研究中心(DFKI)的数字策展技术(DKT)(Rehm and Sasaki,2016,2015)团队参与了两个子任务:子任务A(确定消息的立场)和子任务B(确定消息的准确性)。消息,封闭变体)。在这两种情况下,我们的实现都包括一个多元Logistic回归(最大熵)分类器,以及以后期处理级联方式应用的手写模式和规则(启发式)。我们提供系统性能的详细分析,并报告不属于正式提交内容的系统变型。

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