Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Dynamic modularity in protein interaction networks predicts breast cancer outcome
2009544 citationsCátia Pesquita, Daniel Faria et al.profile →
Semantic Similarity in Biomedical Ontologies
2009517 citationsCátia Pesquita, Daniel Faria et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Daniel Faria's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Faria with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Faria more than expected).
This network shows the impact of papers produced by Daniel Faria. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Faria. The network helps show where Daniel Faria may publish in the future.
Co-authorship network of co-authors of Daniel Faria
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Faria.
A scholar is included among the top collaborators of Daniel Faria based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Daniel Faria. Daniel Faria is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lima, Beatriz Souza Leite Pires de, Daniel Faria, Francisco M. Couto, Isabel F. Cruz, & Cátia Pesquita. (2020). OAEI 2020 results for AML and AMLC.. 154–160.3 indexed citations
5.
Faria, Daniel, et al.. (2019). AML and AMLC Results for OAEI 2019.. 101–106.5 indexed citations
Eckert, Kai, Daniel Faria, Alfio Ferrara, et al.. (2014). Results of the Ontology Alignment Evaluation Initiative 2014. SPIRE - Sciences Po Institutional REpository.11 indexed citations
11.
Pesquita, Cátia, et al.. (2014). Building reference alignments for compound matching of multiple ontologies using OBO cross-products. 172–173.7 indexed citations
12.
Faria, Daniel, Cátia Pesquita, Emanuel Santos, Isabel F. Cruz, & Francisco M. Couto. (2014). AgreementMakerLight 2.0: towards efficient large-scale ontology matching. International Semantic Web Conference. 457–460.7 indexed citations
13.
Faria, Daniel, et al.. (2013). Agreement maker light results for OAEI 2013. International Semantic Web Conference. 101–108.14 indexed citations
14.
Pesquita, Cátia, Daniel Faria, Emanuel Santos, & Francisco M. Couto. (2013). To repair or not to repair: reconciling correctness and coherence in ontology reference alignments. 13–24.35 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.