TY - GEN
T1 - Improving keyphrase extraction using ll-ranking
AU - Popova, Svetlana
AU - Danilova, Vera
AU - Alexandrov, Mikhail
AU - Cardiff, John
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - Keyphrases provide a concise representation of the main content of a document and can be effectively used within information retrieval systems. In the paper, we deal with the keyphrase extraction problem when a given number of keyphrases for a text should be extracted. The research is focused on the keyphrase candidates ranking stage. In the domain, the question remains open of whether the keyphrase extraction quality can be improved by putting limits on the number of phrases of different lengths extracted during candidate ranking. We assume that the quality of resulting keyphrases can be enhanced if we introduce Limitations on the number of phrases of specific Lengths in the resulting set (LL-ranking strategy). The experiments are performed on the well-known INSPEC dataset of scientific abstracts. The obtained results show that the proposed limitations help to significantly increase the quality of extracted keyphrases in terms of P recision and F 1.
AB - Keyphrases provide a concise representation of the main content of a document and can be effectively used within information retrieval systems. In the paper, we deal with the keyphrase extraction problem when a given number of keyphrases for a text should be extracted. The research is focused on the keyphrase candidates ranking stage. In the domain, the question remains open of whether the keyphrase extraction quality can be improved by putting limits on the number of phrases of different lengths extracted during candidate ranking. We assume that the quality of resulting keyphrases can be enhanced if we introduce Limitations on the number of phrases of specific Lengths in the resulting set (LL-ranking strategy). The experiments are performed on the well-known INSPEC dataset of scientific abstracts. The obtained results show that the proposed limitations help to significantly increase the quality of extracted keyphrases in terms of P recision and F 1.
KW - Keyphrase candidates ranking
KW - Keyphrase extraction
KW - Length feature in keyphrase extraction problem
UR - https://www.scopus.com/pages/publications/85076971995
U2 - 10.1007/978-3-030-33695-0_38
DO - 10.1007/978-3-030-33695-0_38
M3 - Conference contribution
AN - SCOPUS:85076971995
SN - 9783030336943
T3 - Advances in Intelligent Systems and Computing
SP - 567
EP - 578
BT - Advances in Intelligent Systems and Computing IV- Selected Papers from the International Conference on Computer Science and Information Technologies, CSIT 2019
A2 - Shakhovska, Natalya
A2 - Medykovskyy, Mykola O.
PB - Springer
T2 - 14th International Scientific and Technical Conference on Computer Science and Information Technologies, CSIT 2019
Y2 - 17 September 2019 through 20 September 2019
ER -