SurfKE: A Graph-Based Feature Learning Framework for Keyphrase Extraction
Description:
Current unsupervised approaches for keyphrase extraction compute a single importance score for each candidate word by considering the number and quality of its associated words in the graph and they are not flexible enough to incorporate multiple types of information. For instance, nodes in a network may exhibit diverse connectivity patterns which are not captured by the graph-based ranking methods. To address this, we present a new approach to keyphrase extraction that represents the document …
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Access:
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Date:
August 2019
Creator:
Florescu, Corina Andreea
Partner:
UNT Libraries