在专家系统里使用决策树并非什么新鲜事物，但是把这种想法和大众外包（crowdsourcing）模式结合在一起实属天才之作。

Using decision trees in expert systems is nothing new, but applying that idea to a crowdsourcing model might possibly be a stroke of genius.

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通过对决策树算法的深入分析，我们围绕着C4.5决策树生成算法建立了一个分类预测系统并实现了与劳动力市场信息管理系统（LMIS）的集成。

With the thorough analysis on the algorithm of decision tree induction, we established a classification and prediction system based on C4.5 and accomplished the integration with the LMIS system.

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实验结果表明，系统所使用的轮廓线向量图像特征也能够较有效地应用于图像方向分类，而机器学习则能够有效地为之建立决策树分类模型。

Using teacher images and machine learning method, an image direction classification model is built as a decision tree. Test results argued the validity of this method.

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