Mining Recipes in Microblog

Abstract

Microblog, as an online communication platform, is becoming more and more popular. Users generate volumes of data everyday and the user generated content contains a lot of useful knowledge such as practical skills and technical expertise. This paper proposes a cross-data method to mine recipes in Microblog. In the proposed method, snippets of text relevant to recipes are firstly extracted from Baidu Encyclopedia. Secondly, the extracted snippets of text are used to train a domain-specific unigram language model. Thirdly, candidate recipes in Microblog are mined based on the unigram language model. Finally, some heuristic rules are used to identify real recipes from the candidate recipes. Experimental results show the effectiveness of the proposed method.