[av_heading heading=’Data, Text and Audio Analytics’ tag=’h2′ color=” style=” padding=’10’]
[av_textblock ]
Data analytics forms an essential step in the data management process, as it is imperative for miscellaneous types of significant applications including business intelligence. In the current era of Big Data, the sheer volume of data poses tremendous challenges for efficient and scalable data analytics. In addition, text analytics is continuously gaining momentum, due to the ever-increasing amount of text made available on the Web by information publishers, in social media by plain users, as well as in open data repositories by governmental agencies. Analyzing this wealth of heterogeneous data calls for new techniques and algorithms for scalable and effective processing, mining and extracting useful knowledge tailored to user preferences and originating from disparate sources. Moreover, new research challenges arise by modern applications that rely on analytics, for instance exploratory data analysis, where users are not aware of the patterns hidden in the underlying data and, perhaps more importantly, they do not know which query to pose. Hence, modern data analysis systems are required that interactively help the user explore the data and gradually form the right query, based on various factors, such as query statistics, previous results, semantic relatedness, or fast retrieval of ranked approximate results.
We have acquired long experience in the field of data analytics and our research record demonstrates strong analytical skills related to all phases of data analysis, from advanced rank-aware query operators to preference-based retrieval of results. Our research agenda covers a wide variety of emerging topics closely related to data and text analytics, ranging from exploratory search and analysis to sentiment analysis.
[/av_textblock]
[av_iconlist position=’left’]
[av_iconlist_item title=’Selected Publications’ link=” linktarget=” icon=’ue84d’ font=’entypo-fontello’]
| Orestis Gkorgkas, Akrivi Vlachou, Christos Doulkeridis and Kjetil Nørvåg. Maximizing Influence of Spatio-Textual Objects Based on Keyword Selection. In Proceedings of 14th International Symposium on Spatial and Temporal Databases (SSTD’15), Seoul, South Korea, August 26-28, 2015. |
| Pikrakis, A., Kopsinis, Y., Chouvardas, S., and Theodoridis, S., “Patterns Classification Formulated as a Missing Data Task: The Audio Genre Classification Case”, Proceedings of the 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015, Brisbane, Queensland, Australia. |
| O. Gkorgkas, A. Vlachou, C. Doulkeridis and K. Nørvåg. Efficient Processing of Exploratory Top-k Joins. In Proceedings of 26th International Conference on Scientific and Statistical Database Management (SSDBM’14), Aalborg, Denmark, June 30 – July 2, 2014. |
| I. Koutsopoulos and M. Halkidi, “Distributed energy-efficient estimation in spatially correlated wireless sensor networks”, Elsevier Computer Communications (Special Issue on Green Networks), 2014. |
| Pikrakis, A., and Sergios Theodoridis. “Speech-music discrimination: A deep learning perspective.” Proceedings of the 22nd European Signal processing Conference (EUSIPCO), pp. 616-620, 2014, Lisbon, Portugal. |
| Giannakopoulos, T., Pikrakis, A., “Introduction to Audio Analysis: a MATLAB Approach”, 2014, Academic Press (imprint of Elsevier Science), 2014, ISBN 978-0080993881. |
| O. Gkorgkas, A. Vlachou, C. Doulkeridis and K. Nørvåg. Discovering Influential Data Objects over Time. In Proceedings of 13th International Symposium on Spatial and Temporal Databases (SSTD’13), Munich, Germany, August 21-23, 2013. |
| A. Vlachou, C. Doulkeridis, K. Nørvåg and Y. Kotidis. Branch-and-Bound Algorithm for Reverse Top-k Queries. In Proceedings of ACM International Conference on Management of Data (SIGMOD’13), New York, USA, June 22-27, 2013. |
| Pikrakis, A., “A deep learning approach to rhythm modeling with applications”, 6th International Workshop on Machine Learning and Music (ΜML 2013), held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2013), Prague, Czech Republic, September 23, 2013. |
| Pikrakis, A. “Audio thumbnailing in video sharing sites”, Proceedings of the 20th European Signal Processing Conference (EUSIPCO), 2012, 27-31 August, 2012, Bucharest, Romania, pp. 1284-1288. |
| Psarakis, M., Pikrakis, A., Dendrinos, G., “FPGA-based Acceleration for Tracking Audio Effects in Movies”, Proceedings of the 20th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), April 29 – May 1, 2012, Toronto, Canda, pp. 85-92. |
| Pikrakis, A., Gómez, F., Oramas, S., Díaz-Báñez, J. M., Mora, J., Escobar-Borrego, F., Gómez, E., Salamon, J., “Tracking Melodic Patterns in Flamenco Singing by Analyzing Polyphonic Music Recordings”, Proceedings of the 13th International Society for Music Information Retrieval Conference (ISMIR), October 8-12, 2012, Porto, Portugal. |
| M.Halkidi. M. Spiliopoulou, A. Pavlou ‘A Semi-supervised Incremental Clustering Algorithm for Streaming Data’, In Proceedings of PAKDD 2012. |
| Gómez, F., Pikrakis, A., Mora, J., Dıaz-Bánez, J. M., Gómez, E., & Escobar, F., “Automatic detection of ornamentation in flamenco”, Proceedings of the Fourth International Workshop on Machine Learning and Music (MML, satellite workshop of the Neural Information Processing Systems conference (NIPS 2011)), December, 16-17, 2011, Sierra Nevada, Spain. |
| A. Vlachou, C. Doulkeridis, N. Polyzotis. Skyline Query Processing over Joins. In Proceedings of ACM International Conference on Management of Data (SIGMOD’11), Athens, Greece, June 12-16. |
| M. Halkidi, D. Spinellis, G. Tsatsaronis, M. Vazirgiannis. “Data mining in software engineering”. Intelligent Data Analysis Journal, 2011. |
| A. Vlachou, C. Doulkeridis, Y. Kotidis and K. Nørvåg. Monochromatic and Bichromatic Reverse Top-k Queries. In IEEE Transactions on Knowledge and Data Engineering (TKDE) (special issue Best of ICDE’10 papers), Vol. 23, Issue 8, pages 1215-1229, August 2011. |
| M. Halkidi, I. Koutsopoulos. ‘Online Clustering of Distributed Streaming Data using Belief Propagation Techniques’, International Conference on Mobile Data Management (MDM), 2011 |
| Giannakopoulos, T., Pikrakis, A., Theodoridis, S., “A multimodal approach to violence detection in video sharing sites”, Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR), August 23-26, 2010, Istanbul, Turkey, pp. 3244-3247. |
| A. Vlachou, C. Doulkeridis, Y. Kotidis and K. Nørvåg. Reverse Top-k Queries. In Proceedings of 26th IEEE International Conference on Data Engineering (ICDE’10), Long Beach, CA, March 1-6, 2010. |
| A. Vlachou, C. Doulkeridis, K. Nørvåg and Y. Kotidis. Identifying the Most Influential Data Objects with Reverse Top-k Queries. In Proceedings of 36th International Conference on Very Large Data Bases (VLDB’10), Singapore, September, 2010. |
| Theodoridis, S., Pikrakis, A., Koutroumbas, K., Cavouras, D., “Introduction to Pattern Recognition: A MATLAB Approach”, Academic Press (imprint of Elsevier Science), 2010, ISBN 978-0123744869. |
[/av_iconlist_item]
[/av_iconlist]