Abstract
Domain keywords extraction is very important for information extraction, information retrieval, classification, clustering, topic detection and tracking, and so on. TextRank is a common graph-based algorithm for keywords extraction. For TextRank, only edge weights are taken into account. We proposed a new text ranking formula that takes into account both edge and node weights of words, named F2N-Rank. Experiments show that F2N-Rank clearly outperformed both TextRank and ATF*DF. F2N-Rank has the highest average precision (78.6%), about 16% over TextRank and 29% over ATF*DF in keywords extraction of Tibetan religion.
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