CQFaRAD: Collaborative Query-Answering Framework for a Research Article Dataspace

Abstract Dataspace systems cope with the problem of integrating a variety of data based on its structures and semantics such as structured, semi-structured, and unstructured data, and returns the best-effort or approximate answers to their users. The existing works on query answering from a dataspac...
Ausführliche Beschreibung

Gespeichert in:
Autor*in:

Singh, Mrityunjay [verfasserIn]

Pandey, Shivam

Saxena, Rohaan

Chaudhary, Maheep

Lal, Niranjan

Format:

E-Artikel

Sprache:

Englisch

Erschienen:

2023

Schlagwörter:

Research Article Dataspace

Pay-as-you-go data integration

Similarity measure

Recommendation system

BERT model

Vector space model

Query-Answering model

Anmerkung:

© The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:

Enthalten in: International journal of information technology - [Singapore] : Springer Singapore, 2017, 16(2023), 3 vom: 30. Sept., Seite 1873-1886

Übergeordnetes Werk:

volume:16 ; year:2023 ; number:3 ; day:30 ; month:09 ; pages:1873-1886

Links:

Volltext

DOI / URN:

10.1007/s41870-023-01518-x

Katalog-ID:

SPR055063470

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