The unsupervised approaches for keyphrase extraction proposed so far have involved a number of techniques, including language modeling (e.g., Tomokiyo and Hurst (2003) ), graph-based ranking (e.g., Zha (2002) ,<cite> Mihalcea and Tarau (2004)</cite> , Wan et al. (2007) , Wan and Xiao (2008) , Liu et al. (2009a) ), and clustering (e.g., Matsuo and Ishizuka (2004) , Liu et al. (2009b) ). While these methods have been shown to work well on a particular domain of text such as short paper abstracts and news articles, their effectiveness and portability across different domains have remained an unexplored issue.