Hierarchical auto-tagging: organizing Q&A knowledge for everyone

Kyosuke Nishida, Ko Fujimura
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引用次数: 7

Abstract

We propose a hierarchical auto-tagging system, TagHats, to improve users' knowledge sharing. Our system assigns three different levels of tags to Q&A documents: category, theme, and keyword. Multiple category tags can organize a document according to multiple viewpoints, and multiple theme and keyword tags can identify what the document is about clearly. Moreover, these hierarchical tags will be helpful in organizing documents to support everyone because different users have different demands in terms of tag specificity. Our system consists of a hierarchical classification method for assigning category and theme tags, a new keyword extraction method that considers the structure of Q&A documents, and a new method for selecting theme tag candidates from each category. Experiments with the documents of Oshiete! goo demonstrate that our system is able to assign hierarchical tags to the documents appropriately and is capable of outperforming baseline methods significantly.
分层自动标记:为每个人组织问答知识
我们提出了一种分层自动标注系统TagHats,以提高用户的知识共享。我们的系统为问答文档分配了三种不同级别的标签:类别、主题和关键字。多个类别标签可以从多个角度组织文档,多个主题和关键字标签可以清楚地识别文档的内容。此外,这些分层标签将有助于组织文档以支持每个人,因为不同的用户在标签专用性方面有不同的需求。我们的系统包括一种用于分配类别和主题标签的分层分类方法,一种考虑问答文档结构的关键字提取方法,以及一种从每个类别中选择候选主题标签的新方法。用奥舍特的文件做实验!我们演示了我们的系统能够适当地为文档分配层次标记,并且能够显著优于基线方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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