Bringing bag-of-phrases to ODP-based text classification

The Open Directory Project (ODP) is a large scale, high quality and publicly available web directory. Many studies and real-world applications build on an ODP-based classifier. However, existing approaches use traditional bag-of-words representation of text to develop an ODP-based classifier and words alone do not always provide atomic units of semantic meaning. In this paper, we propose a novel framework to better understand the semantic meaning of text by bringing bag-of-phrases to ODP-based text classification. The proposed method employs a syntactic tree to extract phrases from ODP and applies a phrase selection method to alleviate the high dimensionality problem of bag-of-phrases. The conducted evaluation results demonstrate that our approach outperforms the state-of-the-art methods in classification performance.