在线社会网络中近似网页识别方法研究

Research on Approximate Web Page Identification Method in Online Social Network

为了提高用户的网络体验和页面检索性能,提出一种基于核心词汇和语义匹配相结合的在线社会网络近似网页识别方法研究.首先从网页中提取特征核心词汇,对文档概念进行分类和合并,并建立相似度特征模型;基于相似度特征模型,构建特征向量,并对特征向量进行检索和存储,实现社会网络中近似网页的识别.实验证明提出的方法能够有效地降低网络噪声,具有良好的识别准确率和召回率.

In order to improve the user＇s Web experience and page retrieval performance, a new method based on key words and semantic matching for online social network is proposed. The first feature extraction of keywords from web pages, classify and merge of document concept, and establish the similarity model; similarity model based on feature vector is constructed, and the retrieval and storage of feature vector, identify the approximate pages in social networks. The experimental results show that the proposed method can effectively reduce the network noise, and has good recognition accuracy and recall rate.