BloSEn：基于后概念聚类的博客搜索引擎
BloSEn: Blog Search Engine Based On Post Concept Clustering
摘要：
本文的研究重点是建立一个博客搜索引擎，它不仅关注关键字搜索，而且包括扩展的搜索功能。它还结合了博客文章的概念聚类，这是基于类别提取的博客文章的语义内容分析。所提出的方法被称为“BloSen（博客搜索引擎）"。它涉及从博客中提取帖子并解析它们以提取博客元素并将它们存储为文档格式的字段。倒排索引正在文档字段上构建。搜索是在索引上诱导的，请求的查询是根据迄今为止从博客帖子中获得的文档来处理的。它目前专注于Blogger和WordPress托管博客，因为这两个托管服务是博客圈中最受欢迎的。提出的BloSen模型进行了实验与原型实现和用户的相关性累积度量值为95.44%的实验结果证实了所提出的模型的效率。
英文摘要：
This paper focuses on building a blog search engine which doesn't focus only on keyword search but includes extended search capabilities. It also incorporates the blog-post concept clustering which is based on the category extracted from the blog post semantic content analysis. The proposed approach is titled as "BloSen (Blog Search Engine)". It involves in extracting the posts from blogs and parsing them to extract the blog elements and store them as fields in a document format. Inverted index is being built on the fields of the documents. Search is induced on the index and requested query is processed based on the documents so far made from blog posts. It currently focuses on Blogger and Wordpress hosted blogs since both these hosting services are the most popular ones in the blogosphere. The proposed BloSen model is experimented with a prototype implementation and the results of the experiments with the user's relevance cumulative metric value of 95.44% confirms the efficiency of the proposed model.
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