Similarity-based classification for big non-structured and semi-structured recipe data

Abstract

In current big data era, there has been an explosive growth of various data. Most of these large volume of data are non-structured or semi-structured (e.g., tweets, weibos or blogs), which are difficult to be managed and organized. Therefore, an effective and efficient classification algorithm for such data is essential and critical. In this article, we focus on a specific kind of non-structured/semi-structured data in our daily life: recipe data. Furthermore, we propose the document model and similarity-based classification algorithm for big non-structured and semistructured recipe data. By adopting the proposed algorithm and system, we conduct the experimental study on a real-world dataset. The results of experiment study verify the effectiveness of the proposed approach and framework.