Exploiting Conversational Features To Detect High-Quality Blog Comments

Canadian AI'11: Proceedings of the 24th Canadian conference on Advances in artificial intelligence(2011)

引用 7|浏览29
暂无评分
摘要
In this work, we present a method for classifying the quality of blog comments using Linear-Chain Conditional Random Fields (CRFs). This approach is found to yield high accuracy on binary classification of high-quality comments, with conversational features contributing strongly to the accuracy. We also present a new corpus of blog data in conversational form, complete with user-generated quality moderation labels from the science and technology news blog Slashdot.
更多
查看译文
关键词
blog comment,blog data,technology news blog Slashdot,conversational feature,conversational form,high accuracy,user-generated quality moderation label,Linear-Chain Conditional Random Fields,binary classification,high-quality comment,high-quality blog comment
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要