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Francesco Gullo
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His research falls into the broad areas of artificial intelligence and data science, with special emphasis on algorithmic aspects, i.e., on formulating, theoretically characterizing, and designing effective yet efficient algorithms
for (novel) problems that are useful to gain insights/information/knowledge from data.
As far as data types, special emphasis has been given to graphs, text, and temporal data, but he has also dealt
with Euclidean data, probabilistic data, and semistructured data. Large-scale data processing and combinatorial
optimization are frequently-occurring keywords in his work.
for (novel) problems that are useful to gain insights/information/knowledge from data.
As far as data types, special emphasis has been given to graphs, text, and temporal data, but he has also dealt
with Euclidean data, probabilistic data, and semistructured data. Large-scale data processing and combinatorial
optimization are frequently-occurring keywords in his work.
Papers82 papers
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Inf. Syst. Frontiers, no. 1 (2021): 101-114
ACM Trans. Knowl. Discov. Data, no. 1 (2021): 1-44
ACM Transactions on Knowledge Discovery from Data (TKDD), no. 1 (2020): 1-40
IEEE Transactions on Network Science and Engineering, pp.1-1, (2020)
Lecture Notes in Computer Science, (2020)
KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Virtual Event..., pp.1371-1381, (2020)
BIAS, pp.152-166, (2020)
Scientific reports, no. 1 (2020): 12529-15
WEB INTELLIGENCE, no. 3 (2019): 177-198
Carlos Alzate,Anna Monreale, Livio Bioglio, Valerio Bitetta,Ilaria Bordino,Guido Caldarelli, Andrea Ferretti,Riccardo Guidotti,Francesco Gullo,Stefano Pascolutti,Ruggero G. Pensa,Céline Robardet
Lecture Notes in Computer Science, (2019)
IEEE Transactions on Knowledge and Data Engineering, no. 11 (2018): 2078-2092
Encyclopedia of Social Network Analysis and Mining. 2nd Ed., (2018)
Cited by5Bibtex
CIKM, (2018): 1003-1012
Cited by2EIBibtex
CIKM, (2018): 107-116
Cristiano Di Crescenzo, Giulia Gavazzi, Giacomo Legnaro, Elena Troccoli,Ilaria Bordino,Francesco Gullo
WIMS, (2017)
Inf. Sci., no. C (2017): 125-137
MIning DAta for financial applicationS (MIDAS 2017), (2017)
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