Tag cloud generation for results of multiple keywords queries

Martin Leginus, Peter Dolog, Ricardo Gomes Lage

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

Abstract

In this paper we study tag cloud generation for retrieved results of multiple keyword queries. It is motivated by many real world scenarios such as personalization tasks, surveillance systems and information retrieval tasks defined with multiple keywords.
We adjust the state-of-the-art tag cloud generation techniques for multiple keywords query results. Consequently, we conduct the extensive evaluation on top of three distinct collaborative tagging systems. The graph-based methods perform significantly better for the Movielens and Bibsonomy datasets. Tag cloud generation based on maximal coverage is more suitable for the Delicious dataset because of the different statistical properties of the dataset

Originalsprog	Engelsk
Titel	Web Engineering : 13th International Conference, ICWE 2013, Aalborg, Denmark, July 8-12, 2013. Proceedings
Redaktører	Florian Daniel, Peter Dolog, Qing Li
Antal sider	15
Vol/bind	7977
Forlag	Springer Publishing Company
Publikationsdato	2013
Sider	233-248
ISBN (Trykt)	978-3-642-39199-6
ISBN (Elektronisk)	978-3-642-39200-9
DOI	https://doi.org/10.1007/978-3-642-39200-9_21
Status	Udgivet - 2013
Begivenhed	13th International Conference on Web Engineering - Aalborg, Danmark Varighed: 8 jul. 2013 → 12 jul. 2013 Konferencens nummer: 13

Konference

Konference	13th International Conference on Web Engineering
Nummer	13
Land/Område	Danmark
By	Aalborg
Periode	08/07/2013 → 12/07/2013

Navn	Lecture Notes in Computer Science
Vol/bind	7977
ISSN	0302-9743

Adgang til dokumentet

10.1007/978-3-642-39200-9_21

http://link.springer.com/chapter/10.1007%2F978-3-642-39200-9_21#

AUB Link

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Citationsformater

Leginus, Martin ; Dolog, Peter ; Lage, Ricardo Gomes. / Tag cloud generation for results of multiple keywords queries. Web Engineering: 13th International Conference, ICWE 2013, Aalborg, Denmark, July 8-12, 2013. Proceedings. red. / Florian Daniel ; Peter Dolog ; Qing Li. Bind 7977 Springer Publishing Company, 2013. s. 233-248 (Lecture Notes in Computer Science, Bind 7977).

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abstract = "In this paper we study tag cloud generation for retrieved results of multiple keyword queries. It is motivated by many real world scenarios such as personalization tasks, surveillance systems and information retrieval tasks defined with multiple keywords.We adjust the state-of-the-art tag cloud generation techniques for multiple keywords query results. Consequently, we conduct the extensive evaluation on top of three distinct collaborative tagging systems. The graph-based methods perform significantly better for the Movielens and Bibsonomy datasets. Tag cloud generation based on maximal coverage is more suitable for the Delicious dataset because of the different statistical properties of the dataset ",

keywords = "tag clouds, information retrieval, summarization",

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Leginus, M, Dolog, P & Lage, RG 2013, Tag cloud generation for results of multiple keywords queries. i F Daniel, P Dolog & Q Li (red), Web Engineering: 13th International Conference, ICWE 2013, Aalborg, Denmark, July 8-12, 2013. Proceedings. bind 7977, Springer Publishing Company, Lecture Notes in Computer Science, bind 7977, s. 233-248, 13th International Conference on Web Engineering, Aalborg, Danmark, 08/07/2013. https://doi.org/10.1007/978-3-642-39200-9_21

Tag cloud generation for results of multiple keywords queries. / Leginus, Martin; Dolog, Peter; Lage, Ricardo Gomes.
Web Engineering: 13th International Conference, ICWE 2013, Aalborg, Denmark, July 8-12, 2013. Proceedings. red. / Florian Daniel; Peter Dolog; Qing Li. Bind 7977 Springer Publishing Company, 2013. s. 233-248 (Lecture Notes in Computer Science, Bind 7977).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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AU - Leginus, Martin

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AU - Lage, Ricardo Gomes

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N2 - In this paper we study tag cloud generation for retrieved results of multiple keyword queries. It is motivated by many real world scenarios such as personalization tasks, surveillance systems and information retrieval tasks defined with multiple keywords.We adjust the state-of-the-art tag cloud generation techniques for multiple keywords query results. Consequently, we conduct the extensive evaluation on top of three distinct collaborative tagging systems. The graph-based methods perform significantly better for the Movielens and Bibsonomy datasets. Tag cloud generation based on maximal coverage is more suitable for the Delicious dataset because of the different statistical properties of the dataset

AB - In this paper we study tag cloud generation for retrieved results of multiple keyword queries. It is motivated by many real world scenarios such as personalization tasks, surveillance systems and information retrieval tasks defined with multiple keywords.We adjust the state-of-the-art tag cloud generation techniques for multiple keywords query results. Consequently, we conduct the extensive evaluation on top of three distinct collaborative tagging systems. The graph-based methods perform significantly better for the Movielens and Bibsonomy datasets. Tag cloud generation based on maximal coverage is more suitable for the Delicious dataset because of the different statistical properties of the dataset

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KW - information retrieval

KW - summarization

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DO - 10.1007/978-3-642-39200-9_21

M3 - Article in proceeding

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Leginus M, Dolog P, Lage RG. Tag cloud generation for results of multiple keywords queries. I Daniel F, Dolog P, Li Q, red., Web Engineering: 13th International Conference, ICWE 2013, Aalborg, Denmark, July 8-12, 2013. Proceedings. Bind 7977. Springer Publishing Company. 2013. s. 233-248. (Lecture Notes in Computer Science, Bind 7977). doi: 10.1007/978-3-642-39200-9_21