browse as linked data

Semantic Web Lab at IC/UFF (UFFSWLab)

Applications

Resources

  • Entity Relatedness Test Data:

    The entity relatedness problem refers to the question of computing the relationship paths that better describe the connectivity between a given entity pair. This dataset supports the evaluation of approaches that address the entity relatedness problem. It covers two familiar domains, music and movies, and uses data available in IMDb and last.fm, which are popular reference datasets in these domains. The dataset contains 20 entity pairs from each of these domains and, for each entity pair, a ranked list with 50 relationship paths. It also contains entity ratings and property relevance scores for the entities and properties used in the paths.
    publications
    1. TALAVERA, José E. T.; CASANOVA, Marco A; NUNES, Bernardo P.; LEME, Luiz André P. Paes and LOPES, Giseli R.. An Entity Relatedness Test Dataset, In: Proceedings of the 16th International Semantic Web Conference (ISWC'17). DOI
    2. TALAVERA Herrera, José Eduardo; CASANOVA, Marco A.; LEME, Luiz André P. Paes. Entity Relatedness Test Data. figshare, (2017). DOI
    3. TALAVERA Herrera, José Eduardo; CASANOVA, Marco A.; LEME, Luiz André P. Paes. Entity Relatedness Test Data to RDF. figshare, (2017). DOI
  • Dataset Descriptions:

    This repository contains descriptions of Linked Data datasets using VoID vocabulary. The descriptions include Linksets, classes, properties and topic categories and mashes up data from DataHub, dataset dumps, VoID files and DBpedia. The DBpedia Spotlight allowed the recognition of named entities in literal values. Each entity is associated with a list of topic categories through the predicate dcterms:subject and each topic category is subsumed by others through the predicate skos:broader. A category c is a topic category of a dataset iff there exists a property path {e dcterms:subject/skos:broader* c.} from a named entity e of the dataset to c in DBpedia.
    publications
    1. NEVES, Angelo B.; LEME, Luiz André P. Paes. Dataset Descriptions. figshare, (2017). DOI
    2. NEVES, Angelo B.; LEME, Luiz André P. Paes. CKAN to VoID App. figshare, (2017). DOI