基于主题Hub值的元搜索
发布时间：2018-11-01 18:09
【摘要】：为了提高元搜索引擎排序结果的质量,提出了成员引擎特征的主题Hub值表示和基于主题Hub值的结果排序算法.特征学习算法利用一组主题关联词对成员引擎的特征进行学习,并表示为主题Hub值的形式.排序算法根据主题Hub值计算结果的全局相关度对结果进行排序.实验结果表明,该模型取得了更好的排序质量.
[Abstract]:In order to improve the quality of the sorting results of the meta search engine, the topic Hub value representation of the member engine features and the result sorting algorithm based on the topic Hub value are proposed. The feature learning algorithm uses a set of topic related words to learn the features of the member engine and expresses them as the Hub value of the topic. The sorting algorithm sorts the results according to the global correlation of the results calculated by the Hub value of the topic. Experimental results show that the model achieves better ranking quality.
【作者单位】： 北京工业大学计算机学院;
【分类号】：TP391.3
[Abstract]:In order to improve the quality of the sorting results of the meta search engine, the topic Hub value representation of the member engine features and the result sorting algorithm based on the topic Hub value are proposed. The feature learning algorithm uses a set of topic related words to learn the features of the member engine and expresses them as the Hub value of the topic. The sorting algorithm sorts the results according to the global correlation of the results calculated by the Hub value of the topic. Experimental results show that the model achieves better ranking quality.
【作者单位】： 北京工业大学计算机学院;
【分类号】：TP391.3
【参考文献】
相关期刊论文 前3条
1 周茜,赵明生,扈e，
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