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Connections across scientific publications based on semantic annotations


Castro, Leyla Jael Garcia; Berlanga, Rafael; Rebholz-Schuhmann, Dietrich; Garcia, Alexander (2013). Connections across scientific publications based on semantic annotations. In: 3rd Workshop on Semantic Publishing (SePublica 2013), 10th Extended Semantic Web Conference, Montpellier, France, 26 May 2013 - 26 May 2013, 51-62.

Abstract

Abstract. The core information from scientific publications is encoded in natural language text and monolithic documents; therefore it is not well integrated with other structured and unstructured data resources. The text format requires additional processing to semantically interlink the publications and to finally reach interoperability of contained data. Data infrastructures such as the Linked Open Data initiative based on the Resource Description Framework support the connectivity of data from scientific publications once the identification of concepts and relations has been achieved, and the content has been interconnected semantically. In this manuscript we produce and analyze the semantic annotations in scientific articles to investigate on the interconnectivity across the articles. In our initial experiment based on articles from PubMed Central we demonstrate the means and the results leading to the interconnectivity using annotations of Medical Subject Headings concepts, Unified Medical Language System terms, and semantic abstractions of relations. We conclude that the different methods would contribute to different types of relatedness between articles that could be later used in recommendation systems based on semantic links across a network of scientific publications.

Abstract. The core information from scientific publications is encoded in natural language text and monolithic documents; therefore it is not well integrated with other structured and unstructured data resources. The text format requires additional processing to semantically interlink the publications and to finally reach interoperability of contained data. Data infrastructures such as the Linked Open Data initiative based on the Resource Description Framework support the connectivity of data from scientific publications once the identification of concepts and relations has been achieved, and the content has been interconnected semantically. In this manuscript we produce and analyze the semantic annotations in scientific articles to investigate on the interconnectivity across the articles. In our initial experiment based on articles from PubMed Central we demonstrate the means and the results leading to the interconnectivity using annotations of Medical Subject Headings concepts, Unified Medical Language System terms, and semantic abstractions of relations. We conclude that the different methods would contribute to different types of relatedness between articles that could be later used in recommendation systems based on semantic links across a network of scientific publications.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:26 May 2013
Deposited On:23 Oct 2013 08:23
Last Modified:05 Apr 2016 17:04
Series Name:CEUR Workshop Proceedings
Number:994
ISSN:1613-0073
Free access at:Official URL. An embargo period may apply.
Official URL:http://ceur-ws.org/Vol-994/paper-05.pdf
Permanent URL: https://doi.org/10.5167/uzh-82214

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TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

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