I have recently received my Ph.D. in Computer Science from
UFMG,
Brazil.
Currently, I am a professor of Computer Science at UFMG (Adjunto I). My research focuses on machine learning, and large scale parallel and distributed data mining algorithms and applications.
Office: 4049 Computer Science Dept. Phone: (31)3409-5579 Email: a d r i a n o v [AT] dcc.ufmg.br (remove spaces in name and replace [AT] with appropriate symbol)
Exploiting Temporal Locality to Determine User Bias in Microblogging Platforms. P. Calais, L. Cerf, T. Porto, A. Veloso, W. Meira Jr. and V. Almeida. Journal of Information and Data Management 2011. pdf
Calibrated Lazy Associative Classification. A. Veloso, W. Meira, M. Zaki, M. Goncalves and H. Mossri. Information Sciences 2011. link
Learning to Rank using Query-Level Rules. A. Veloso, M. Goncalves, W. Meira Jr. and H. Mossri. Journal of Information and Data Management 2010. pdf
Competence-Conscious Associative Classification. A. Veloso, W. Meira, M. Zaki, M. Goncalves. Statistical Analysis and Data Mining 2009. pdf
Parallel and Distributed Methods for Incremental Frequent Itemset Mining. M. Otey, A. Veloso, C. Wang, S. Parthasarathy and W. Meira. IEEE Transactions on Systems, Man and Cybernetics, Part B 2004. pdf
Conferences
Spam Detection Using Web Page Content: a New Battleground. M. Ribeiro, P. Calais, D. Guedes, W. Meira Jr., A. Veloso, C. Hoepers, K. Steding-Jessen, and M. Chaves. CEAS 2011. pdf
From Bias to Opinion: A Transfer-Learning Approach to Real-Time Sentiment Analysis. P. Calais, A. Veloso, W. Meira Jr. and V. Almeida. SIGKDD 2011. pdf
Rule-Based Active Sampling for Learning to Rank
. R. Silva, A. Veloso, M. Goncalves. PKDD 2011. pdf
Learning Sentiment Streams with Training Expansion and Demand-Driven Projection. I. Silva, J. Gomide, A. Veloso, R. Ferreira and W. Meira Jr. SIGIR 2011. pdf
Dengue surveillance based on a computational model of spatio-temporal locality of Twitter. J. Gomide, A. Veloso, W. Meira Jr., F. Benevenuto, V. Almeida, F. Ferraz, M. Teixeira. ACM WEBSCI 2011. pdf
Demand-Driven Tag Recommendation. G. Menezes, A. Veloso, E. Moura, J. Almeida, G. Pappa, M. Goncalves, A. Lacerda, F. Belem and N. Ziviani. PKDD 2010. pdf
Active Learning Genetic Programming for Record Deduplication. J. de Freitas, G. Pappa, M. Goncalves, A. Veloso, E. Moura and A. da Silva. CEC 2010. pdf
Effective Self-Training Author Name Disambiguation in Scholarly Digital Libraries
. A. Ferreira, A. Veloso, M. Goncalves, A. Laender. JCDL 2010. pdf
Learning to Rank for Content-Based Image Retrieval. F. Faria, A. Veloso, E. Valle, H. Almeida, M. Goncalves, R. Torres, W. Meira Jr. MIR 2010. pdf
SyGAR - A Synthetic Data Generator for Evaluating Name Disambiguation Methods. A. Ferreira, J. Almeida, A. Laender, M. Goncalves, A. Veloso. ECDL 2009. pdf
The Metric Dillema: Competence-Conscious Associative Classification. A. Veloso, M. Zaki, W. Meira, M. Goncalves. SDM 2009. pdf
Calibrated Lazy Associative Classification. A. Veloso, W. Meira, M. Zaki. SBBD 2008. pdf
Learning to Rank at Query-Time using Association Rules. A. Veloso, H. Mossri, M. Goncalves, W. Meira. SIGIR 2008. pdf
Efficient On-Demand Opinion Mining. A. Veloso, W. Meira. SBBD 2007. pdf
Multi-Label Lazy Associative Classification. A. Veloso, W. Meira, M. Goncalves and M. Zaki. PKDD 2007. pdf
Automatic Moderation of Comments in a Large On-line Journalistic Environment. A. Veloso, W. Meira, T. Macambira, D. Guedes and H. Almeida. ICWSM 2007. pdf
Lazy Associative Classification. A. Veloso, W. Meira and M. Zaki. ICDM 2006. pdf
Multi-Evidence, Multi-Criteria, Lazy Associative Document Classification. A. Veloso, W. Meira, M. Cristo, M. Goncalves and M. Zaki. CIKM 2006. pdf
Lazy Associative Classification for Content-Based Spam Detection. A. Veloso and W. Meira. LaWEB 2006. pdf
Rule Generation and Rule Selection Techniques for Cost-Sensitive Associative Classification. A. Veloso and W. Meira. SBBD 2005. pdf ps.gz
Asynchronous and Anticipatory Filter-Stream Based Parallel Algorithm for Frequent Itemset Mining. A. Veloso, W. Meira, R. Ferreira, D. Guedes and S. Parthasarathy. PKDD 2004. pdf
Mining Frequent Itemsets in Distributed and Dynamic Databases. M. Otey, A. Veloso, C. Wang, S. Parthasarathy and W. Meira. ICDM 2003. pdf
Efficient, Accurate and Privacy-Preserving Data Mining for Frequent Itemsets in Distributed Databases. A. Veloso, W. Meira, S. Parthasarathy and M. B. de Carvalho. SBBD 2003. pdf ps.gz
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases. A. Veloso, W. Meira, S. Parthasarathy. SBAC 2003. pdf ps.gz
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets. A. Veloso, M. Otey, W. Meira and S. Parthasarathy. HiPC 2003. pdf ps.gz
Mining Reliable Models of Associations in Dynamic Databases. A. Veloso, W. Meira and M. B. de Carvalho. SBBD 2002. pdf
Efficiently Mining Approximate Models of Associations in Evolving Databases. A. Veloso, B. Gusmao, W. Meira, M. B. de Carvalho, S. Parthasarathy and M. Zaki. PKDD 2002. pdf ps.gz
Real World Association Rule Mining. A. Veloso, B. Gusmao, W. Meira, M. B. de Carvalho. BNCOD 2002. pdf ps.gz
Mining Frequent Itemsets in Evolving Databases. A. Veloso, W. Meira, M. B. de Carvalho, S. Parthasarathy and M. Zaki. SDM 2002. pdf ps.gz
Mining Twitter for Opinions and Feelings. M. Ribeiro, A. Veloso, W. Meira Jr., G. Pappa, L. Cherchiglia, L. Teixeira, G. Brunoro. SBBD 2010.
Workshops and Technical Reports
Parallel, Incremental and Interactive Frequent Itemset Mining. A. Veloso, W. Meira, M. B. de Carvalho, S. Parthasarathy and M. Zaki. SIAM High Performance Data Mining Workshop 2003. pdf ps.gz
Knowledge Management on Association Rule Mining. A. Veloso, W. Meira, M. B. de Carvalho. Data Mining and Knowledge Management Workshop 2001. pdf ps.gz
Incremental Techniques for Mining Dynamic and Distributed Databases. M. Otey, A. Veloso, C. Wang, S. Parthasarathy and W. Meira. OSU-TR48 2003. pdf
