Maria-Esther Vidal

Publications256
h-index22
Citations2,219
Highly Influential Citations128
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ANAPSID: An Adaptive Query Processing Engine for SPARQL Endpoints
TLDR
We present ANAPSID, an adaptive query engine for SPARQL endpoints that adapts query execution schedulers to data availability and run-time conditions. Expand
  • 192
  • 32
  • PDF
A Heuristic-Based Approach for Planning Federated SPARQL Queries
TLDR
A large number of SPARQL endpoints are available to access the Linked Open Data cloud, but query capabilities still remain very limited. Expand
  • 43
  • 6
  • PDF
Old is Gold: Linguistic Driven Approach for Entity and Relation Linking of Short Text
TLDR
We present the Falcon approach which effectively maps entities and relations within a short text to its mentions of a background knowledge graph. Expand
  • 31
  • 5
  • PDF
GADES: A Graph-based Semantic Similarity Measure
TLDR
We present GADES, a Graph-bAseD Entity Similarity measure for knowledge graphs, and show that it is able to obtain similarity values more correlated with respect to gold standards. Expand
  • 22
  • 5
MULDER: Querying the Linked Data Web by Bridging RDF Molecule Templates
TLDR
The increasing number of RDF data sources that allow for querying Linked Data via Web services form the basis for federated SPARQL query processing. Expand
  • 18
  • 5
Wrapper generation for Web accessible data sources
TLDR
In this paper, we present technology to define and (automatically) generate wrappers for Web accessible data sources. Expand
  • 102
  • 4
  • PDF
Towards a Knowledge Graph for Science
TLDR
The document-centric workflows in science have reached (or already exceeded) the limits of adequacy. Expand
  • 45
  • 4
Benchmarking Federated SPARQL Query Engines: Are Existing Testbeds Enough?
TLDR
We evaluate FedBench, the most comprehensive testbed up to now, and empirically probe the need of considering additional dimensions and variables that may have an impact on the behavior of these systems. Expand
  • 43
  • 4
  • PDF
Drug-Target Interaction Prediction Using Semantic Similarity and Edge Partitioning
TLDR
We present a novel method that combines a data mining framework for link prediction, semantic knowledge (similarities) from ontologies or semantic spaces, and an algorithmic approach to partition the edges of a heterogeneous graph. Expand
  • 36
  • 3
On the Selection of SPARQL Endpoints to Efficiently Execute Federated SPARQL Queries
TLDR
We consider the problem of source selection and query decomposition in federations of SPARQL endpoints, where query decompositions of aSPARQL query should reduce execution time and maximize answer completeness. Expand
  • 18
  • 3