Massive volumes of images of museums or art collections, or made available by artists and photographers, more and more often, are available on the web, along with some metadata, essential for their characterization and retrieval. A set of (scored) keywords/keyphrases that characterize the semantic content of the documents should be, automatically or manually, extracted and/or associated. We present here a work-in-progress to evaluate different methods for the unsupervised keyword extraction to Italian and English datasets. In the paper datasets, algorithms and approaches are presented and discussed together with some preliminary results referred to relatedness of terms.

Unsupervised automatic keyphrases extraction algorithms: Experimentations on paintings

I Gagliardi;MT Artese
2019

Abstract

Massive volumes of images of museums or art collections, or made available by artists and photographers, more and more often, are available on the web, along with some metadata, essential for their characterization and retrieval. A set of (scored) keywords/keyphrases that characterize the semantic content of the documents should be, automatically or manually, extracted and/or associated. We present here a work-in-progress to evaluate different methods for the unsupervised keyword extraction to Italian and English datasets. In the paper datasets, algorithms and approaches are presented and discussed together with some preliminary results referred to relatedness of terms.
2019
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
978-3-030-11682-8
Unsupervised Automatic Keyphrase Extraction
Evaluation
Information Retrieval
TextRank
RAKE
Tf-Idf
Latent Semantic Indexing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/361477
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