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    • 1. 发明授权
    • Cross-market model adaptation with pairwise preference data
    • 跨市场模型适应与成对偏好数据
    • US08489590B2
    • 2013-07-16
    • US12966983
    • 2010-12-13
    • Yi ChangZhaohui ZhengFernando David DiazJing Bai
    • Yi ChangZhaohui ZhengFernando David DiazJing Bai
    • G06F7/00G06F17/30
    • G06F17/30864
    • Embodiments are directed towards generating market-specific ranking models by leveraging target market specific pairwise preference data. The pairwise preference data includes market-specific training examples, while a ranking model from another market captures the common characteristics of the resulting ranking model. In one embodiment, the ranking model is trained by applying a Tree Based Ranking Function Adaptation (TRADA) algorithm to multi-grade labeled training data, such as editorially generated training data. Then, contradictions between the TRADA generated ranking model and target-market specific pairwise preference data are identified. For each identified contradiction, new training data is generated to correct the contradiction. Then, in one embodiment, an algorithm such as TRADA is applied to the existing ranking model and the new training data to generate a new ranking model.
    • 实施例旨在通过利用目标市场特定的成对偏好数据来产生市场特定的排名模型。 成对偏好数据包括市场特定的培训示例,而来自另一个市场的排名模型捕获了所得到的排名模型的共同特征。 在一个实施例中,通过将基于树的排序函数适应(TRADA)算法应用于诸如编辑生成的训练数据的多等级标记的训练数据来训练排名模型。 然后,确定了TRADA产生的排名模型和目标市场特定成对偏好数据之间的矛盾。 对于每个确定的矛盾,产生新的训练数据以纠正矛盾。 然后,在一个实施例中,诸如TRADA的算法被应用于现有的排名模型和新的训练数据以生成新的排名模型。
    • 2. 发明申请
    • CROSS-MARKET MODEL ADAPTATION WITH PAIRWISE PREFERENCE DATA
    • 交叉市场模型适配与配对偏好数据
    • US20120150855A1
    • 2012-06-14
    • US12966983
    • 2010-12-13
    • Yi ChangZhaohui ZhengFernando David DiazJing Bai
    • Yi ChangZhaohui ZhengFernando David DiazJing Bai
    • G06F17/30
    • G06F17/30864
    • Embodiments are directed towards generating market-specific ranking models by leveraging target market specific pairwise preference data. The pairwise preference data includes market-specific training examples, while a ranking model from another market captures the common characteristics of the resulting ranking model. In one embodiment, the ranking model is trained by applying a Tree Based Ranking Function Adaptation (TRADA) algorithm to multi-grade labeled training data, such as editorially generated training data. Then, contradictions between the TRADA generated ranking model and target-market specific pairwise preference data are identified. For each identified contradiction, new training data is generated to correct the contradiction. Then, in one embodiment, an algorithm such as TRADA is applied to the existing ranking model and the new training data to generate a new ranking model.
    • 实施例旨在通过利用目标市场特定的成对偏好数据来产生市场特定的排名模型。 成对偏好数据包括市场特定的培训示例,而来自另一个市场的排名模型捕获了所得到的排名模型的共同特征。 在一个实施例中,通过将基于树的排序函数适应(TRADA)算法应用于诸如编辑生成的训练数据的多等级标记的训练数据来训练排名模型。 然后,确定了TRADA产生的排名模型和目标市场特定成对偏好数据之间的矛盾。 对于每个确定的矛盾,产生新的训练数据以纠正矛盾。 然后,在一个实施例中,诸如TRADA的算法被应用于现有的排名模型和新的训练数据以生成新的排名模型。
    • 9. 发明申请
    • METHOD FOR IMPROVING OPERATION DENSITY OF RAIL VEHICLES AND PREVENTING HEAD-ON COLLISION AND REAR-ENDING COLLISION
    • 改善铁路车辆运行密度和防止碰撞和后期碰撞的方法
    • US20130327897A1
    • 2013-12-12
    • US13825262
    • 2011-08-09
    • Wei BaiJing BaiQing BaiBaolong Feng
    • Wei BaiJing BaiQing BaiBaolong Feng
    • B61L23/26
    • B61L23/26B61L21/10B61L23/14B61L23/18B61L23/30
    • The present invention provides a method for improving operation density of rail vehicles and for preventing head-on collision and rear-ending collision. Said method divides a rail line into equidistant electronic zones, the length of a zone being greater than the shortest safe distance between two running vehicles. Said method installs a locomotive passing detection alarm device in each zone, when a locomotive travels at high speed on the rail, the locomotive passing detection alarm device corresponding to the zone occupied by the locomotive itself will simultaneously access adjacent front and back zones, and determine whether the two adjacent zones are simultaneously occupied by locomotives. If the two adjacent. zones are simultaneously occupied by locomotives, the locomotive passing alarm device will send an alarm signal to the locomotives to warn or otherwise take measures. The aforesaid method can avoid locomotive head-on collision and rear-end collision and increase transportation density according to the vehicle speed and distance at the same time, thus improving the transportation efficiency.
    • 本发明提供了一种提高轨道车辆的运行密度和防止碰撞和后端碰撞的方法。 所述方法将铁路线划分成等距离的电子区域,区域的长度大于两辆运行车辆之间的最短安全距离。 所述方法在每个区域安装机车通过检测报警装置,当机车在轨道上高速行驶时,对应于机车本身占据的区域的机车通过检测报警装置将同时访问相邻的前后区域,并确定 两个相邻区域是否同时被机车占据。 如果两个相邻。 机车同时占用机车,机车通过报警装置将向机车发出报警信号,以警告或采取措施。 上述方法可以避免机车前后碰撞和后端碰撞,同时根据车速和距离增加运输密度,从而提高运输效率。