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    <dc:date>2026-04-03T18:52:13Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10174/39301">
    <title>Partial DRS, an Intermediate Representation, to Generate SPARQL Queries from NL Questions</title>
    <link>http://hdl.handle.net/10174/39301</link>
    <description>Title: Partial DRS, an Intermediate Representation, to Generate SPARQL Queries from NL Questions
Authors: Varagnolo, Davide; Melo, Dora
Editors: Antonacopoulos, A
Abstract: This paper presents a tool to build an intermediate representation, Partial DRS, a Language-Independent Partial Discourse Representation Structure (DRS), that can be used to generate SPARQL queries from Natural Language (NL) Questions. The Partial DRS builder consists of two main steps: creating a Universal Dependencies (UD) parse and transforming the UD parse using a set of rules into a graph with discourse referents as edges and syntactic roles as arcs labels. The Partial DRS of a natural language sentence can be interpreted within a target application domain modelled as a domain ontology, enabling the semantic interpretation of the syntactic roles represented by the graph arc labels. The domain ontology uses the annotations on Object and Data Properties, and Classes to represent natural language and domain-dependent information. These annotations include syntactic role preferences and vocabulary. An evaluation of the proposed system is presented, showing very promising results in the specific DBLP domain.</description>
    <dc:date>2024-09-24T23:00:00Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10174/39300">
    <title>Translating Natural Language Questions into CIDOC-CRM SPARQL Queries to Access Cultural Heritage Knowledge Bases</title>
    <link>http://hdl.handle.net/10174/39300</link>
    <description>Title: Translating Natural Language Questions into CIDOC-CRM SPARQL Queries to Access Cultural Heritage Knowledge Bases
Authors: Varagnolo, Davide; Melo, Dora; Pimenta Rodrigues, Irene
Editors: Rodriguez Echavarria, Karina
Abstract: To explore information on the semantic web, SPARQL queries or DL-queries are suitable tools. However, users interested in exploring the content of such knowledge bases often find it challenging to employ formal query languages, as this requires familiarity with the target domain’s representation model. To address these challenges, a question-answering system that automatically translates natural language questions into SPARQL queries, over the Smithsonian American Art Museum CIDOC-CRM representation is presented. The proposed approach uses an ontology, named Query Ontology, defined to represent the natural language concepts and relations specific to the question’s domain. This system’s architecture uses a traditional natural language processing symbolic approach, with a pipeline of modules for the syntactic, semantic, and pragmatic analysis. An evaluation of the proposed system is presented and shows very promising results.</description>
    <dc:date>2025-04-18T23:00:00Z</dc:date>
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    <title>Book of Abstracts: International Workshop on Mathematics and Physical Sciences</title>
    <link>http://hdl.handle.net/10174/35379</link>
    <description>Title: Book of Abstracts: International Workshop on Mathematics and Physical Sciences
Authors: Minhós, Feliz; Bezzeghoud, Mourad; Abreu, Salvador; Carapau, Fernando; Correira, Paulo
Abstract: This book-proceeding comprises the results of various comprehensive Mathematical and&#xD;
Physical Sciences-based studies accepted for presentation and discussion during the&#xD;
1st Mathematical and Physical Sciences International Workshop in Évora, in 2023 (Mat-&#xD;
Phys23). The MatPhys23, organized under the auspices of University of Évora throughout&#xD;
the CIMA - Research Center in Mathematics and Applications, the ICT - Institute of Earth&#xD;
Sciences and the NOVA-LINCS - NOVA Laboratory for Informatics and Computer Science&#xD;
(Évora branch). This Workshop brought together many well-known mathematicians,&#xD;
physicists and engineers from University of Beira Interior (UBI, Portugal), University of&#xD;
Cabo Verde (UCV, Cabo Verde), Montclair State University (MSU, NJ, USA) and University&#xD;
of Évora (UÉ, Portugal). This book-proceeding volume involves 24 abstracts on&#xD;
the latest trending and significant challenges in mathematics and physical sciences. The&#xD;
works presented focus on the following areas: statistical and mathematical methods that&#xD;
are relevant to biology, medical and biomedical sciences, computer science, economics,&#xD;
social sciences, music, environmental sciences, climatology, engineering, industry, fluid&#xD;
mechanics and their applications, numerical simulations in various physical, geophysical,&#xD;
chemical, biological and engineering applications. In addition to the usual scientific interaction&#xD;
between participants, this meeting has the presence of PhD students, which we&#xD;
consider relevant. Considering the original contents, aims, and methodologies of all these valuable studies,&#xD;
it is believed that the topical outputs are of interest to all researchers, practitioners, and&#xD;
students and would mainly provide new scientific insights and knowledge for geoscientists&#xD;
and engineers.</description>
    <dc:date>2023-06-16T23:00:00Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10174/33448">
    <title>Quantum and Digital Annealing for the Quadratic Assignment Problem</title>
    <link>http://hdl.handle.net/10174/33448</link>
    <description>Title: Quantum and Digital Annealing for the Quadratic Assignment Problem
Authors: Codognet, Philippe; Diaz, Daniel; Abreu, Salvador
Abstract: The Quadratic Assignment Problem is a a classical constrained optimization problem used to model many real-life applications. We present experiments in solving the Quadratic Assignment Problem by means of Quantum Annealing and Quantum-inspired Annealing. We describe how to model this classical combinatorial problem in terms of QUBO (Quadratic Unconstrained Binary optimization) for implementing it on hardware solvers based on quantum or quantum-inspired annealing (D-Wave, Fujitsu Digital Annealing Unit and Fixstars Amplify Annealing Engine). We present performance result for these implementations and compare them with well established metaheuristic solvers on classical hardware, such as Robust Tabu Search and External Optimization.</description>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
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