Incremental Inference of Provenance Types

Autor:	David Kohan Marzagão, Luc Moreau, Trung Dong Huynh
Rok vydání:	2021
Předmět:	Provenance Information retrieval Computer science Encoding (memory) Batch processing Neighbourhood (graph theory) Inference Context (language use) Key features
Zdroj:	Lecture Notes in Computer Science ISBN: 9783030809591 IPAW
DOI:	10.1007/978-3-030-80960-7_9
Popis:	Long-running applications nowadays are increasingly instrumented to continuously log provenance. In that context, we observe an emerging need for processing fragments of provenance continuously produced by applications. Thus, there is an increasing requirement for processing of provenance incrementally, while the application is still running, to replace batch processing of a complete provenance dataset available only after the application has completed. A type of processing of particular interest is summarising provenance graphs, which has been proposed as an effective way of extracting key features of provenance and storing them in an efficient manner. To that goal, summarisation makes use of provenance types, which, in loose terms, are an encoding of the neighbourhood of nodes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::52d6811d44aa86e1e3859b00d850b850 https://doi.org/10.1007/978-3-030-80960-7_9 Zobrazit plný text záznamu