Hierarchical Auto-Tagging: Organizing QA Knowledge for Everyone

摘要

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.