Theme-Based Summarization for RDF Datasets
| Autor: | Mohamad Rihany, Zoubida Kedad, Stéphane Lopes |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
050101 languages & linguistics
Information retrieval Exploit Computer science 05 social sciences 02 engineering and technology computer.file_format Automatic summarization Node (computer science) 0202 electrical engineering electronic engineering information engineering Rdf graph 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Relevance (information retrieval) RDF computer Theme (computing) |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030590505 DEXA (2) |
| DOI: | 10.1007/978-3-030-59051-2_21 |
| Popis: | A growing number of RDF datasets are published on the web. These datasets can be viewed as graphs; querying, analyzing and visualizing such data graphs are critical challenges facing the applications willing to use them, especially when their size is important. Summarization can help addressing these challenges. In this paper, we present a summarization approach which exploits the underlying themes of an RDF graph, and builds a global summary from the theme summaries. To this end, we propose some node relevance metrics. We present some experiments to illustrate the effectiveness of our approach. |
| Databáze: | OpenAIRE |
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