A Position-Biased PageRank Algorithm for Keyphrase Extraction

Proceedings of the AAAI Conference on Artificial IntelligencePublished 12 February 2017Open access

Corina Florescu, Cornelia Caragea

DOI10.1609/aaai.v31i1.11082

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Citations76

SJR score0.13

SNIP0.00

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TL;DR

PositionRank is proposed, an unsupervised graph-based approach to keyphrase extraction that incorporates information from all positions of a word's occurrences into a biased PageRank to extract keyphrases.

Abstract

Given the large amounts of online textual documents available these days, e.g., news articles and scientific papers, effective methods for extracting keyphrases, which provide a high-level topic description of a document, are greatly needed.We propose PositionRank, an unsupervised graph-based approach to keyphrase extraction that incorporates information from all positions of a word's occurrences into a biased PageRank to extract keyphrases. Our model obtains remarkable improvements in performance over strong baselines.

Keywords

Computer Science

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