IJCAI 2022poster0 citations
KRAKEN: A Novel Semantic-Based Approach for Keyphrases Extraction
Abstract
We propose KRAKEN, a novel approach for the extraction of keyphrases from texts. To this aim, KRAKEN makes use of distributional semantics to identify, as completely as possible, representative portions of documents, i.e. keyphrases. In addition, we define novel metrics to assess a weighted significance to the keyphrases extracted from a document, identifying the most important ones by assessing their semantic similarity with the text of the document they belong to.
Speech & Natural Language Processing (SNLP): General
BibTeX
@inproceedings{ijcai2022p825,
title = {KRAKEN: A Novel Semantic-Based Approach for Keyphrases Extraction},
author = {D'Amico, Simone},
booktitle = {Proceedings of the Thirty-First International Joint Conference on
Artificial Intelligence, {IJCAI-22}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Lud De Raedt},
pages = {5845--5846},
year = {2022},
month = {7},
note = {Doctoral Consortium},
doi = {10.24963/ijcai.2022/825},
url = {https://doi.org/10.24963/ijcai.2022/825},
}