1,542 research outputs found
Challenges in Bridging Social Semantics and Formal Semantics on the Web
This paper describes several results of Wimmics, a research lab which names
stands for: web-instrumented man-machine interactions, communities, and
semantics. The approaches introduced here rely on graph-oriented knowledge
representation, reasoning and operationalization to model and support actors,
actions and interactions in web-based epistemic communities. The re-search
results are applied to support and foster interactions in online communities
and manage their resources
Foundational Challenges in Automated Data and Ontology Cleaning in the Semantic Web
The application of automated reasoning
systems to data cleaning in the Semantic Web raises
many challenges on the foundational basis of cleaning
agent design. The authors discuss some of them. They
finally argue that logic trust in the Semantic Web can
only be achieved if it is based on certified reasoning.Junta de AndalucĂa TIC-13
An ontology-aided, natural language-based approach for multi-constraint BIM model querying
Being able to efficiently retrieve the required building information is
critical for construction project stakeholders to carry out their engineering
and management activities. Natural language interface (NLI) systems are
emerging as a time and cost-effective way to query Building Information Models
(BIMs). However, the existing methods cannot logically combine different
constraints to perform fine-grained queries, dampening the usability of natural
language (NL)-based BIM queries. This paper presents a novel ontology-aided
semantic parser to automatically map natural language queries (NLQs) that
contain different attribute and relational constraints into computer-readable
codes for querying complex BIM models. First, a modular ontology was developed
to represent NL expressions of Industry Foundation Classes (IFC) concepts and
relationships, and was then populated with entities from target BIM models to
assimilate project-specific information. Hereafter, the ontology-aided semantic
parser progressively extracts concepts, relationships, and value restrictions
from NLQs to fully identify constraint conditions, resulting in standard SPARQL
queries with reasoning rules to successfully retrieve IFC-based BIM models. The
approach was evaluated based on 225 NLQs collected from BIM users, with a 91%
accuracy rate. Finally, a case study about the design-checking of a real-world
residential building demonstrates the practical value of the proposed approach
in the construction industry
e-Social Science and Evidence-Based Policy Assessment : Challenges and Solutions
Peer reviewedPreprin
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