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Towards a Ranking Model for Semantic Layers over Digital Archives

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

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OriginalspracheEnglisch
Titel des Sammelwerks2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9781538638613
PublikationsstatusVeröffentlicht - Juli 2017
Veranstaltung17th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL) - Toronto, Kanada
Dauer: 19 Juni 201723 Juni 2017

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NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries
ISSN (Print)1552-5996

Abstract

Archived collections of documents (like newspaper archives) serve as important information sources for historians, journalists, sociologists and other interested parties. Semantic Layers over such digital archives allow describing and publishing metadata and semantic information about the archived documents in a standard format (RDF), which in turn can be queried through a structured query language (e.g., SPARQL). This enables to run advanced queries by combining metadata of the documents (like publication date) and content-based semantic information (like entities mentioned in the documents). However, the results returned by structured queries can be numerous and also they all equally match the query. Thus, there is the need to rank these results in order to promote the most important ones. In this paper, we focus on this problem and propose a ranking model that considers and combines: i) the relativeness of documents to entities, ii) the timeliness of documents, and iii) the relations among the entities.

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Towards a Ranking Model for Semantic Layers over Digital Archives. / Fafalios, Pavlos; Kasturia, Vaibhav; Nejdl, Wolfgang.
2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7991617 (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Fafalios, P, Kasturia, V & Nejdl, W 2017, Towards a Ranking Model for Semantic Layers over Digital Archives. in 2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017., 7991617, Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, Institute of Electrical and Electronics Engineers Inc., 17th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), Toronto, Kanada, 19 Juni 2017. https://doi.org/10.1109/JCDL.2017.7991617
Fafalios, P., Kasturia, V., & Nejdl, W. (2017). Towards a Ranking Model for Semantic Layers over Digital Archives. In 2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017 Artikel 7991617 (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/JCDL.2017.7991617
Fafalios P, Kasturia V, Nejdl W. Towards a Ranking Model for Semantic Layers over Digital Archives. in 2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 7991617. (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries). doi: 10.1109/JCDL.2017.7991617
Fafalios, Pavlos ; Kasturia, Vaibhav ; Nejdl, Wolfgang. / Towards a Ranking Model for Semantic Layers over Digital Archives. 2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017. Institute of Electrical and Electronics Engineers Inc., 2017. (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries).
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abstract = "Archived collections of documents (like newspaper archives) serve as important information sources for historians, journalists, sociologists and other interested parties. Semantic Layers over such digital archives allow describing and publishing metadata and semantic information about the archived documents in a standard format (RDF), which in turn can be queried through a structured query language (e.g., SPARQL). This enables to run advanced queries by combining metadata of the documents (like publication date) and content-based semantic information (like entities mentioned in the documents). However, the results returned by structured queries can be numerous and also they all equally match the query. Thus, there is the need to rank these results in order to promote the most important ones. In this paper, we focus on this problem and propose a ranking model that considers and combines: i) the relativeness of documents to entities, ii) the timeliness of documents, and iii) the relations among the entities.",
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AU - Nejdl, Wolfgang

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