2010, ‘A Semi-supervised key phrase extraction approach: learning from title phrases through a document semantic network
Decong Li, Sujian Li, Wenjie Li, Wei Wang, Weiguang Qu · 2010
It is a fundamental and important task to ex-tract key phrases from documents. Generally, phrases in a document are not independent in delivering the content of the document. In or-der to capture and make better use of their re-lationships in key phrase extraction, we sug-gest exploring the Wikipedia knowledge to model a document as a semantic network, where both n-ary and binary relationships among phrases are formulated. Based on a commonly accepted assumption that the title of a document is always elaborated to reflect the content of a document and consequently key phrases tend to have close semantics to the title, we propose a novel semi-supervised key phrase extraction approach in this paper by computing the phrase importance in the se-mantic network, through which the influence of title phrases is propagated to the other phrases iteratively. Experimental results dem-onstrate the remarkable performance of this approach. 1