Fuzzy keyword ontology for annotating and searching event reports

Juhani Hirvonen; Teemu Tommila; Antti Pakonen; C. Carlsson; M. Fedrizzi; R. Fullér

Fuzzy keyword ontology for annotating and searching event reports

Juhani Hirvonen, Teemu Tommila, Antti Pakonen, C. Carlsson, M. Fedrizzi, R. Fullér

BA1621 AI-aided systems engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

7 Citations (Scopus)

Abstract

This paper defines and applies a fuzzy keyword ontology to annotate and search event reports in a database. The ontology is developed by superimposing a fuzzy partonomy on fuzzy classifications. The claim is that fuzzy keywords will help us find event reports even if the event description is incomplete or imprecise and that this will provide benefits in finding the relevant problem reports. This will save time and costs when working with queries on large data- and knowledge bases.

Original language	English
Title of host publication	Proceedings of the International Conference on Knowledge Engineering and Ontology Development, KEOD 2010
Place of Publication	Portugal
Publisher	SciTePress
Pages	251-256
ISBN (Print)	978-989-8425-29-4
Publication status	Published - 2010
MoE publication type	A4 Article in a conference publication
Event	International Conference on Knowledge Engineering and Ontology Development KEOD 2010 - Valencia, Italy Duration: 25 Oct 2010 → 28 Oct 2010

Conference

Conference	International Conference on Knowledge Engineering and Ontology Development KEOD 2010
Abbreviated title	KEOD 2010
Country	Italy
City	Valencia
Period	25/10/10 → 28/10/10

Keywords

Fuzzy ontology
Fuzzy partonomy
Fuzzy reasoning schemes
Knowledge mobilisation
Semantic web.

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Cite this

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title = "Fuzzy keyword ontology for annotating and searching event reports",

abstract = "This paper defines and applies a fuzzy keyword ontology to annotate and search event reports in a database. The ontology is developed by superimposing a fuzzy partonomy on fuzzy classifications. The claim is that fuzzy keywords will help us find event reports even if the event description is incomplete or imprecise and that this will provide benefits in finding the relevant problem reports. This will save time and costs when working with queries on large data- and knowledge bases.",

keywords = "Fuzzy ontology, Fuzzy partonomy, Fuzzy reasoning schemes, Knowledge mobilisation, Semantic web.",

author = "Juhani Hirvonen and Teemu Tommila and Antti Pakonen and C. Carlsson and M. Fedrizzi and R. Full{\'e}r",

note = "Project code: 18101; International Conference on Knowledge Engineering and Ontology Development KEOD 2010, KEOD 2010 ; Conference date: 25-10-2010 Through 28-10-2010",

year = "2010",

language = "English",

isbn = "978-989-8425-29-4",

pages = "251--256",

booktitle = "Proceedings of the International Conference on Knowledge Engineering and Ontology Development, KEOD 2010",

publisher = "SciTePress",

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Hirvonen, J, Tommila, T, Pakonen, A, Carlsson, C, Fedrizzi, M & Fullér, R 2010, Fuzzy keyword ontology for annotating and searching event reports. in Proceedings of the International Conference on Knowledge Engineering and Ontology Development, KEOD 2010. SciTePress, Portugal, pp. 251-256, International Conference on Knowledge Engineering and Ontology Development KEOD 2010, Valencia, Italy, 25/10/10.

Fuzzy keyword ontology for annotating and searching event reports. / Hirvonen, Juhani; Tommila, Teemu; Pakonen, Antti; Carlsson, C.; Fedrizzi, M.; Fullér, R.

Proceedings of the International Conference on Knowledge Engineering and Ontology Development, KEOD 2010. Portugal : SciTePress, 2010. p. 251-256.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Fuzzy keyword ontology for annotating and searching event reports

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AU - Tommila, Teemu

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AU - Carlsson, C.

AU - Fedrizzi, M.

AU - Fullér, R.

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AB - This paper defines and applies a fuzzy keyword ontology to annotate and search event reports in a database. The ontology is developed by superimposing a fuzzy partonomy on fuzzy classifications. The claim is that fuzzy keywords will help us find event reports even if the event description is incomplete or imprecise and that this will provide benefits in finding the relevant problem reports. This will save time and costs when working with queries on large data- and knowledge bases.

KW - Fuzzy ontology

KW - Fuzzy partonomy

KW - Fuzzy reasoning schemes

KW - Knowledge mobilisation

KW - Semantic web.

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EP - 256

BT - Proceedings of the International Conference on Knowledge Engineering and Ontology Development, KEOD 2010

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