TSAKE: A topical and structural automatic keyphrase extractor

This paper introduces TSAKE, a novel approach for automatic keyphrase extraction that leverages both N-gram topical models and co-occurrence graphs. Unlike traditional methods, TSAKE weights edges in the co-occurrence graph using the topic model and applies network analysis to identify finer-grained sub-topics. By incorporating these insights, TSAKE outperforms baseline techniques and state-of-the-art models in keyphrase extraction tasks

Recommended citation: Javad Rafiei-Asl, and Ahmad Nickabadi. "TSAKE: A topical and structural automatic keyphrase extractor." Applied soft computing 58 (2017): 620-630. https://doi.org/10.1016/j.asoc.2017.05.014