文本浏览是伴随着因特网上日益增多的在线文本而出现的辅助阅读机制,本文给出了基于潜在语义索引的文本浏览机制。它吸取了潜在语义索引和概念标注的优点,利用潜在语义索引,减少词汇间的“斜交”现象,在语义空间上进行项与项、文本与文本、项与文本之间的相似度计算。利用概念词典将文本特征项按语义分类,给予层次分类以确定的含义。最后,实现以分层概念为基础的信息导航。
Abstract
Text browsing is the assistant reading mechanism to help users browse the online texts. Text browsing based on Latent Semantic Indexing (LSI) is presented in this paper ,and it combines LSI with concept tagging to improve the efficiency of users reading. It applies LSI to reduce the skew intersections and calculates the similarity between terms and texts based on the semantic space ,it also divides the terms into several semantic classes and determines the meanings of classes. In additional ,it implements the information navigation based on conceptual tree.
关键词
文本浏览 /
潜在语义索引 /
概念标注 /
特征抽取
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Key words
text browsing /
latent semantic indexing /
concept tagging /
text feature extraction
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参考文献
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脚注
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基金
国家自然科学基金资助项目(编号:69675019),国家教委博士点基金资助项目
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