A Text Feature Based Automatic Keyword Extraction Method for Single Documents

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Campos, R (Author) Other; Mangaravite, V (Author) Other; Pasquali, A (Author) Other; Jorge, AM (Author) FCUP; Nunes, C (Author) Other; Jatowt, A (Author) Other

Conference proceedings International

Title: ADVANCES IN INFORMATION RETRIEVAL (ECIR 2018)

Pages: 684-691

40th European Conference on Information Retrieval Research (ECIR)

Grenoble, FRANCE, MAR 26-29, 2018

Indexing

ISI Web of Knowledge - 34 Citations

Scopus - 55 Citations

Other information

Authenticus ID: P-00N-NF3

DOI: 10.1007/978-3-319-76941-7_63

Abstract (EN): In this work, we propose a lightweight approach for keyword extraction and ranking based on an unsupervised methodology to select the most important keywords of a single document. To understand the merits of our proposal, we compare it against RAKE, TextRank and SingleRank methods (three well-known unsupervised approaches) and the baseline TF. IDF, over four different collections to illustrate the generality of our approach. The experimental results suggest that extracting keywords from documents using our method results in a superior effectiveness when compared to similar approaches.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8