基于可伸缩语义网络距离的Web多维信息识别算法

Web信息复杂程度不断加深,多维度、高复杂度的信息越来越多,信息特征的多元化弊端日益呈现。Web特征的表述越来越困难。为解决这一问题,提出了一种基于可伸缩语义网络距离的Web多维信息识别算法。在Web特征表述过程中,运用语义网络强度的多维信息表达能力,对多维信息进行表达,运用一种可伸缩模糊语言距离的概念,满足Web信息的多样性。完成多维信息的高效挖掘。实验结果表明,该算法能有效减少Web信息挖掘事件,提高了挖掘的准确性,取得了满意的效果。

Dynamic Web services discovery based on similarity computation

A new approach for dynamic Web services discovery based on similarity computation in the treatment of massive Web information resource is put forward. Firstly, three kinds of service description information, textual, semantic and structural information, were modeled to compute the similarity of services. Then a novel dynamic Web services discovery mechanism was provided and the experiment on it was carried out. Results show that the new approach achieves considerable performance on precision and efficiency metrics for dynamic Web services discovery.