Crowd Sourced Semantic Enrichment (CroSSE) for knowledge driven querying of digital resources

Giacomo Cavallo, Francesco Di Mauro, Paolo Pasteris, Maria Luisa Sapino, Kasim Candan

Research output: Contribution to journalArticle

Abstract

Today, most information sources provide factual, objective knowledge, but they fail to capture personalized contextual knowledge which could be used to enrich the available factual data and contribute to their interpretation, in the context of the knowledge of the user who queries the system. This would require a knowledge framework which can accommodate both objective data and semantic enrichments that capture user provided knowledge associated to the factual data in the database. Unfortunately, most conventional DBMSs lack the flexibilities necessary (a) to prevent the data and metadata, evolve quickly with changing application requirements and (b) to capture user-provided and/or crowdsourced data and knowledge for more effective decision support. In this paper, we present CrowdSourced Semantic Enrichment (CroSSE) knowledge framework which allows traditional databases and semantic enrichment modules to coexist. CroSSE provides a novel Semantically Enriched SQL (SESQL) language to enrich SQL queries with information from a knowledge base containing semantic annotations. We describe CroSSE and SESQL with examples taken from our SmartGround EU project.

Original languageEnglish (US)
JournalJournal of Intelligent Information Systems
DOIs
StatePublished - Jan 1 2019

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Keywords

  • Crowd-sourcing
  • Data integration framework
  • Semantic enrichment

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Crowd Sourced Semantic Enrichment (CroSSE) for knowledge driven querying of digital resources. / Cavallo, Giacomo; Di Mauro, Francesco; Pasteris, Paolo; Sapino, Maria Luisa; Candan, Kasim.

In: Journal of Intelligent Information Systems, 01.01.2019.

Research output: Contribution to journalArticle

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