Artem Grotov and I will be teaching a half-day tutorial on online learning to rank for information retrieval at SIGIR 2016. During the past 10–15 years offline learning to rank has had a tremendous influence on information retrieval, both scientifically and in practice. Recently, as the limitations of offline learning to rank for information retrieval…
Neu-IR: SIGIR 2016 Workshop on Neural Information Retrieval
SIGIR 2016 will feature a workshop on Neural Information Retrieval. In recent years, deep neural networks have yielded significant performance improvements in application areas such as speech recognition and computer vision. They have also had an impact in natural language applications such as machine translation, image caption generation and conversational agents. Our focus with the…
We’re hiring: PhD students and postdoc in learning to rank for IR
We’re looking for two PhD students and a postdoc to work on a project on learning to rank for information retrieval. The goal of the project is to lay the foundations for contextual LTR methods, which automatically construct the right ranking features based on the query context. The project will use data collected through natural…
We’re hiring: PhD student or postdoc Citizen Data Science
We’re looking to hire a PhD student or postdoc to work on citizen data science. Citizens increasingly share their lives online. Through social media experiences, opinions and reports of events are shared. In parallel, residents of cities such as Amsterdam collect data using widely available sensor technologies, to measure air quality, traffic, or trash on…
WWW 2016 papers online
We have three full papers at WWW this year. They are all online now: Alexey Borisov, Pavel Serdyukov, and Maarten de Rijke. Using metafeatures to increase the effectiveness of latent semantic models in web search. In WWW 2016: 25th International World Wide Web Conference, page 1081–1091. ACM, April 2016. Bibtex, PDF @inproceedings{borisov-using-2016, author = {Borisov,…
NWO grant on learning to rank for information retrieval
Good news from NWO today. I received a grant from NWO to support two PhD students and a postdoc to work on learning to rank (LTR) for information retrieval. The goal is to lay the foundations for contextual LTR methods, which automatically construct the right ranking features based on the query context. The project will…
Media coverage in Le Monde
On the occasion of the 15th anniversary of Wikipedia, French newspaper Le Monde has devoted a full page to Wikipedia, which includes a discussion of the role of Wikipedia in research, especially around semantic search and the knowledge graph. In this setting our work on semantic analysis of microblogs, entity linking, and linking content for…
Nikos Voskarides wins 2014/2015 STIL Thesis Award
Congratulations to my PhD student Nikos Voskarides for winning the 2014/2015 STIL Thesis Award for his MSc thesis “Explaining relationships between entities.” The prize was awarded on December 18, 2015, at CLIN-26 in Amsterdam. His MSc thesis was supervised by Edgar Meij and Manos Tsagkias.
WSDM 2016 paper on dynamic collective entity representations for entity ranking online
The following WSDM 2016 paper is online now: David Graus, Manos Tsagkias, Wouter Weerkamp, Edgar Meij, and Maarten de Rijke. Learning dynamic collective entity representations for entity ranking. In WSDM 2016: The 9th International Conference on Web Search and Data Mining, page 595–604. ACM, February 2016. Bibtex, PDF @inproceedings{graus-dynamic-2016, author = {Graus, David and Tsagkias,…
Three full papers accepted at WWW 2016
Good news. Three full papers were accepted at the 25th Word Wide Web Conference: Alexey Borisov, Pavel Serdyukov and Maarten de Rijke: Using Metafeatures to Increase the Effectiveness of Latent Semantic Models in Web Search Alexey Borisov, Ilya Markov, Maarten de Rijke and Pavel Serdyukov: A Distributed Representation Approach to Modeling User Browsing Behavior in…