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Authors: Felice Ferrara and Carlo Tasso

Affiliation: University of Udine, Italy

Keyword(s): Keyphrase Extraction, Social Tagging, Keyphrase Recommendation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Soft Computing ; Symbolic Systems ; Web Mining

Abstract: Social tagging systems allow people to classify resources by using a set of freely chosen terms named tags. However, by shifting the classification task from a set of experts to a larger and not trained set of people, the results of the classification are not accurate. The lack of control and guidelines generates noisy tags (i.e. tags without a clear semantics) which deteriorate the precision of the user generated classifications. In order to face this limitation several tools have been proposed in the literature for suggesting to the users tags which properly describe a given resource. In this paper we propose to suggest n-grams (named keyphrases) by following the idea that sequences of two/three terms can better face potential ambiguities. More specifically, in this work, we identify a set of features which characterize n-grams able to describe meaningful aspects reported in Web pages. By means of these features we developed a mechanism which can support people to manually classify Web pages by automatically suggesting meaningful keyphrases expressed in English. (More)

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Paper citation in several formats:
Ferrara, F. and Tasso, C. (2012). A Keyphrase Extraction Approach for Social Tagging Systems. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2012) - KDIR; ISBN 978-989-8565-29-7; ISSN 2184-3228, SciTePress, pages 362-365. DOI: 10.5220/0004144203620365

@conference{kdir12,
author={Felice Ferrara. and Carlo Tasso.},
title={A Keyphrase Extraction Approach for Social Tagging Systems},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2012) - KDIR},
year={2012},
pages={362-365},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004144203620365},
isbn={978-989-8565-29-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2012) - KDIR
TI - A Keyphrase Extraction Approach for Social Tagging Systems
SN - 978-989-8565-29-7
IS - 2184-3228
AU - Ferrara, F.
AU - Tasso, C.
PY - 2012
SP - 362
EP - 365
DO - 10.5220/0004144203620365
PB - SciTePress

- Science and Technology Publications, Lda.
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