Victoria Uren

Dr. Victoria Uren

orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2006 in Journal of Web Semantics
Verified
Journal Article
Closed access
VUVictoria Uren
Victoria Uren
PCPhilipp Cimiano
Philipp Cimiano
JIJosé Iria
José Iria
SHSiegfried Handschuh
Siegfried Handschuh
MVMaria Vargas-Vera
Maria Vargas-Vera
FCFabio Ciravegna
Fabio Ciravegna

1 January 2006
Verified
Book Chapter
Closed access
PDF file
YLYuangui Lei
Yuangui Lei
VUVictoria Uren
Victoria Uren
EMEnrico Motta
Enrico Motta

30 June 2007 in Journal of Web Semantics
Verified
Journal Article
Closed access
VLVanessa Lopez
Vanessa Lopez
VUVictoria Uren
Victoria Uren
EMEnrico Motta
Enrico Motta
MPMichele Pasin
Michele Pasin

1 January 2011 in Semantic Web: – Interoperability, Usability, Applicability
Verified
Journal Article
Closed access
PDF file
VLVanessa Lopez
Vanessa Lopez
VUVictoria Uren
Victoria Uren
MSMarta Sabou
Marta Sabou
EMEnrico Motta
Enrico Motta
With the recent rapid growth of the Semantic Web (SW), the processes of searching and querying content that is both massive in scale and heterogeneous have become increasingly challenging. User-friendly interfaces, which can support end users in quer

1 May 2017 in Industrial Marketing Management
Verified
Journal Article
Open access
VSVictor Guang Shi
Victor Guang Shi
TBTim Baines
Tim Baines
JBJames Baldwin
James Baldwin
KRKeith Ridgway
Keith Ridgway
PPPanagiotis Petridis
Panagiotis Petridis
DADaniel Andrews
Daniel Andrews

1 August 2008
Verified
Conference Paper
Closed access
MFMiriam Fernandez
Miriam Fernandez
VLVanessa Lopez
Vanessa Lopez
MSMarta Sabou
Marta Sabou
VUVictoria Uren
Victoria Uren
DVDavid Vallet
David Vallet
PCPablo Castells
Pablo Castells
While semantic search technologies have been proven to work well in specific domains, they still have to confront two main challenges to scale up to the Web in its entirety. In this work we address this issue with a novel semantic search system that a) provides the user with the capability to query Semantic Web information using natural language, by means of an ontology-based Question Answering (QA) system [14] and b) complements the specific answers retrieved during the QA process with a ranked list of documents from the Web [3]. Our results show that ontology-based semantic search capabilities can be used to complement and enhance keyword search technologies.