P
P Serdyukov
info
Please Note
<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
2 records found
1
Report on ECIR 2016
38th European Conference on Information Retrieval
Journal article
(2016)
-
Nicola Ferro, Fabio Crestani, Stefano Mizzaro, Giorgio Maria Di Nunzio, Claudia Hauff, Omar Alonso, P Serdyukov, Gianmaria Silvello, Marie-Francine Moens, Josiane Mothe, Fabrizio Silvestri, Jaana Kekäläinen, Paolo Rosso, Paul Clough, Gabriella Pasi, Christina Lioma
The 38th European Conference on Information Retrieval took place from the 20th to the 23rd of March 2016 in Padua, Italy. This report summarizes the conference in terms of the presented keynotes, scientific and social programme, industry day, tutorials, workshops and student support.
...
The 38th European Conference on Information Retrieval took place from the 20th to the 23rd of March 2016 in Padua, Italy. This report summarizes the conference in terms of the presented keynotes, scientific and social programme, industry day, tutorials, workshops and student support.
The Benchmark as a Research Catalyst
Charting the Progress of Geo-prediction for Social Multimedia
Book chapter
(2015)
-
Martha Larson, Pascal Kelm, Vanessa Murdock, Gerald Friedland, Adam Rae, Claudia Hauff, Bart Thomee, Michele Trevisiol, Jaeyoung Choi, Olivier van Laere, Steven Schockaert, Pavel Serdyukov
Benchmarks have the power to bring research communities together to focus on specific research challenges. They drive research forward by making it easier to systematically compare and contrast new solutions, and evaluate their performance with respect to the existing state of the art. In this chapter, we present a retrospective on the Placing Task, a yearly challenge offered by the MediaEval Multimedia Benchmark. The Placing Task, launched in 2010, is a benchmarking task that requires participants to develop algorithms that automatically predict the geolocation of social multimedia (videos and images). This chapter covers the editions of the Placing Task offered in 2010–2013, and also presents an outlook onto 2014. We present the formulation of the task and the task dataset for each year, tracing the design decisions that were made by the organizers, and how each year built on the previous year. Finally, we provide a summary of future directions and challenges for multimodal geolocation, and concluding remarks on how benchmarking has catalyzed research progress in the research area of geolocation prediction for social multimedia.
...
Benchmarks have the power to bring research communities together to focus on specific research challenges. They drive research forward by making it easier to systematically compare and contrast new solutions, and evaluate their performance with respect to the existing state of the art. In this chapter, we present a retrospective on the Placing Task, a yearly challenge offered by the MediaEval Multimedia Benchmark. The Placing Task, launched in 2010, is a benchmarking task that requires participants to develop algorithms that automatically predict the geolocation of social multimedia (videos and images). This chapter covers the editions of the Placing Task offered in 2010–2013, and also presents an outlook onto 2014. We present the formulation of the task and the task dataset for each year, tracing the design decisions that were made by the organizers, and how each year built on the previous year. Finally, we provide a summary of future directions and challenges for multimodal geolocation, and concluding remarks on how benchmarking has catalyzed research progress in the research area of geolocation prediction for social multimedia.