Casual users are the estimator. We know that the Score Function of SEEKER with ranking result sets is related to several factors such as sizeof(T), but they greatly influent accuracy of ranking in case of non-normal.
用户是对结果集的最终评价者,然而SEEKER系统中用于对结果排序的评分函数与相关因子如sizeof(T)等有关,这些因子未标准化的情况下,大大影响排序准确度。
参考来源 - 基于关系数据库的关键词模糊查询及结果集排序策略研究The results show that the score function of complexes is effective and simple for rational protein docking and its design.
分于对接结果表明，此打分函数能有效并简单的应用于任意蛋白质分子对接。
参考来源 - 蛋白质二聚体相互作用和识别的计算机模拟·2,447,543篇论文数据，部分数据来源于NoteExpress
A score function for optimization based on maximum mutual information entropy with odditional restriction is proposed.
提出了基于最大互信息熵且具有奇数约束的优化得分函数。
Finally, we define a score function to sort all the alternatives and select the best one.
决策规则，最后定义一个评分函数对整个方案集进行排序和优选。
Then regression method can be used by all the common factors of the score function, and can be integrated score obtained for each company.
最后可利用回归法得到各个公因子的得分函数，并可求得各个公司的综合得分。
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