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.
Automatic feedback in online learning environments: A systematic literature review
2021238 citationsAnderson Pinheiro Cavalcanti, Fred Freitas 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 Fred Freitas'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 Fred Freitas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fred Freitas more than expected).
This network shows the impact of papers produced by Fred Freitas. 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 Fred Freitas. The network helps show where Fred Freitas may publish in the future.
Co-authorship network of co-authors of Fred Freitas
This figure shows the co-authorship network connecting the top 25 collaborators of Fred Freitas.
A scholar is included among the top collaborators of Fred Freitas 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 Fred Freitas. Fred Freitas is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cavalcanti, Anderson Pinheiro, Rafael Ferreira Mello, Dragan Gašević, & Fred Freitas. (2023). Towards Explainable Prediction Feedback Messages Using BERT. International Journal of Artificial Intelligence in Education. 34(3). 1046–1071.1 indexed citations
Freitas, Fred, et al.. (2015). OCIP - An OntoClean Evaluation System Based on a Constraint Prolog Extension Language..2 indexed citations
6.
Freitas, Fred, et al.. (2014). A Method to Develop Description Logic Ontologies Iteratively with Automatic Requirement Traceability.. Description Logics. 646–658.
7.
Freitas, Fred, et al.. (2014). Towards a framework for ontology learning from interactions in natural language and reasoning. 120–132.1 indexed citations
Freitas, Fred, et al.. (2013). An Ontology-based System to Support Distributed Software Development. International Conference on Software Engineering Advances. 178–183.1 indexed citations
11.
Freitas, Fred, et al.. (2013). A Method to Develop Description Logic Ontologies Iteratively Based on Competency Questions: an Implementation.. 142–153.2 indexed citations
Freitas, Fred. (2011). A Connection Method for Inferencing over the Description Logic ALC.. Description Logics.2 indexed citations
16.
Freitas, Fred, et al.. (2010). Dr. Pierre: Um Chatterbot com Intenção e Personalidade Baseado em Ontologias para Apoiar o Ensino de Psiquiatria. Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação - SBIE). 1(1).2 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.