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|Booktitle=Web Engineering, 16th International Conference, ICWE 2016, Lugano, Switzerland, June 6-9, 2016. Proceedings | |Booktitle=Web Engineering, 16th International Conference, ICWE 2016, Lugano, Switzerland, June 6-9, 2016. Proceedings | ||
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|Publisher=Springer International Publishing | |Publisher=Springer International Publishing | ||
|Address=Cham | |Address=Cham | ||
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|Series=Lecture Notes in Computer Science | |Series=Lecture Notes in Computer Science | ||
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Aktuelle Version vom 25. Oktober 2016, 15:36 Uhr
LinkSUM: Using Link Analysis to Summarize Entity Data
LinkSUM: Using Link Analysis to Summarize Entity Data
Published: 2016
Juni
Herausgeber: Bozzon, Alessandro and Cudré-Mauroux, Philippe and Pautasso, Cesare
Buchtitel: Web Engineering, 16th International Conference, ICWE 2016, Lugano, Switzerland, June 6-9, 2016. Proceedings
Ausgabe: 9671
Reihe: Lecture Notes in Computer Science
Seiten: 244-261
Verlag: Springer International Publishing
Erscheinungsort: Cham
Referierte Veröffentlichung
Kurzfassung
The amount of structured data published on the Web is constantly growing. A significant part of this data is published in accordance to the Linked Data principles. The explicit graph structure enables machines and humans to retrieve descriptions of entities and discover information about relations to other entities. In many cases, descriptions of single entities include thousands of statements and for human users it becomes difficult to comprehend the data unless a selection of the most relevant facts is provided.
In this paper we introduce LinkSUM, a lightweight link-based approach for the relevance-oriented summarization of knowledge graph entities. LinkSUM optimizes the combination of the PageRank algorithm with an adaption of the Backlink method together with new approaches for predicate selection. Both, quantitative and qualitative evaluations have been conducted to study the performance of the method in comparison to an existing entity summarization approach. The results show a significant improvement over the state of the art and lead us to conclude that prioritizing the selection of related resources leads to better summaries.
ISBN: 978-3-319-38791-8
Download: Media:LinkSUM.pdf
DOI Link: 10.1007/978-3-319-38791-8_14
Web Science und Wissensmanagement
Vernetzte Daten, Semantische Suche, Maschinelles Lernen, Entitätszusammenfassung