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.
Countries citing papers authored by Fábio Crestani
Since
Specialization
Citations
This map shows the geographic impact of Fábio Crestani'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 Fábio Crestani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fábio Crestani more than expected).
This network shows the impact of papers produced by Fábio Crestani. 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 Fábio Crestani. The network helps show where Fábio Crestani may publish in the future.
Co-authorship network of co-authors of Fábio Crestani
This figure shows the co-authorship network connecting the top 25 collaborators of Fábio Crestani.
A scholar is included among the top collaborators of Fábio Crestani 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 Fábio Crestani. Fábio Crestani is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ríssola, Esteban A., et al.. (2019). Predicting Relevant Conversation Turns for Improved Retrieval in Multi-Turn Conversational Search.. Text REtrieval Conference.1 indexed citations
3.
Losada, David E., Fábio Crestani, & Javier Parapar. (2017). CLEF 2017 eRisk Overview: Early Risk Prediction on the Internet: Experimental Foundations.. CLEF (Working Notes).17 indexed citations
Aliannejadi, Mohammad, Ida Mele, & Fábio Crestani. (2016). Venue Appropriateness Prediction for Contextual Suggestion.. Text REtrieval Conference.4 indexed citations
6.
Aliannejadi, Mohammad, et al.. (2015). University of Lugano at TREC 2015: Contextual Suggestion and Temporal Summarization Tracks. Text REtrieval Conference.7 indexed citations
7.
Inches, Giacomo & Fábio Crestani. (2012). Overview of the International Sexual Predator Identification Competition at PAN-2012..50 indexed citations
Gerani, Shima, et al.. (2010). University of Lugano at TREC 2010. Text REtrieval Conference.4 indexed citations
10.
Carman, Mark, Robert Gwadera, Shima Gerani, et al.. (2009). University of Lugano at TREC 2009 Blog Track. Text REtrieval Conference.2 indexed citations
Crestani, Fábio, et al.. (2008). A Bayesian Decay Model for Suspect Prioritisation Based on Geographical Profiling. 29(1). 69–76.1 indexed citations
13.
Gerani, Shima, et al.. (2008). University of Lugano at TREC 2008 Blog Track. View.5 indexed citations
14.
Herrera‐Viedma, Enrique, Gabriella Pasi, & Fábio Crestani. (2006). Soft Computing in Web Information Retrieval: Models and Applications (Studies in Fuzziness and Soft Computing). Springer eBooks.3 indexed citations
15.
Callan, Jamie, Fábio Crestani, & Mark Sanderson. (2004). Distributed Multimedia Information Retrieval: Sigir 2003 Workshop on Distributed Information Retrieval, Toronto, Canada, August 2003: Revised, Selected, and Invited Papers (Lecture Notes in Computer Science, 2924). Springer eBooks.3 indexed citations
Crestani, Fábio, et al.. (2002). User Centered Evaluation of an Automatically Constructed Hyper-TextBook. Journal of educational multimedia and hypermedia. 11(1). 3–19.9 indexed citations
Crestani, Fábio, Ian Ruthven, Mark Sanderson, & C. J. van Rijsbergen. (1995). The Troubles with Using a Logical Model of IR on a Large Collection of Documents. Strathprints: The University of Strathclyde institutional repository (University of Strathclyde).18 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.