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Pavel Serdyukov

Pavel Serdyukov

D-Index & Metrics

Computer Science

D-Index
31
Citations
3961
World Ranking
13692
National Ranking
4

Overview

Pavel Serdyukov is a researcher affiliated with Yandex in the Russian Federation. Their work spans interdisciplinary fields primarily within Computer Science and Physics and Astronomy.

The main fields of study covered in their research include:

  • Computer Science
  • Physics and Astronomy

Within these, their subfields of study focus on:

  • Artificial Intelligence
  • Information Systems
  • Statistical and Nonlinear Physics
  • Computer Vision and Pattern Recognition
  • Geography, Planning and Development

The research topics addressed by Pavel Serdyukov involve:

  • Recommender Systems and Techniques
  • Advanced Image and Video Retrieval Techniques
  • Geographic Information Systems Studies
  • Complex Network Analysis Techniques
  • Opinion Dynamics and Social Influence
  • Spam and Phishing Detection
  • Text and Document Classification Technologies

Serdyukov has contributed to several papers, notably:

  • "Personalized Landmark Recommendation Based on Geotags from Photo Sharing Sites," 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Predicting the Audience Size of a Tweet," 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "METHODS OF OBTAINING INFORMATION ABOUTTHE THREE-DIMENSIONAL SCENE TO SOLVE PROBLEMSOF DETERMINING THE SPATIAL POSITION OF OBJECTSWITH A REGULAR STRUCTURE," 2022, Izvestiâ ÛFU. Tehničeskie nauki

The frequent co-authors who have collaborated with Serdyukov include:

  • Yue Shi
  • Alan Hanjalić
  • Martha Larson
  • Andrey Kupavskii
  • Alexey Umnov

Publication venues that have featured Serdyukov's work multiple times are:

  • Proceedings of the International AAAI Conference on Web and Social Media
  • Izvestiâ ÛFU. Tehničeskie nauki

Best Publications

  • Placing flickr photos on a map

    Pavel Serdyukov;Vanessa Murdock;Roelof van Zwol

  • Overview of the TREC 2010 Entity Track

    Krisztian Balog;Pavel Serdyukov;Arjen P. de Vries

  • Context-Aware Neural Machine Translation Learns Anaphora Resolution

    Elena Voita;Elena Voita;Pavel Serdyukov;Rico Sennrich;Rico Sennrich;Ivan Titov;Ivan Titov

  • Expertise Retrieval

    Krisztian Balog;Yi Fang;Maarten de Rijke;Pavel Serdyukov

  • Prediction of retweet cascade size over time

    Andrey Kupavskii;Liudmila Ostroumova;Alexey Umnov;Svyatoslav Usachev

  • A Neural Click Model for Web Search

    Alexey Borisov;Ilya Markov;Maarten de Rijke;Pavel Serdyukov

  • Overview of the TREC 2009 Entity Track

    Krisztian Balog;Arjen P. de Vries;Pavel Serdyukov;Paul Thomas

  • Modeling multi-step relevance propagation for expert finding

    Pavel Serdyukov;Henning Rode;Djoerd Hiemstra

  • Automatic tagging and geotagging in video collections and communities

    Martha Larson;Mohammad Soleymani;Pavel Serdyukov;Stevan Rudinac

  • Using flickr geotags to predict user travel behaviour

    Maarten Clements;Pavel Serdyukov;Arjen P. de Vries;Marcel J.T. Reinders

  • The where in the tweet

    Wen Li;Pavel Serdyukov;Arjen P. de Vries;Carsten Eickhoff

  • Click model-based information retrieval metrics

    Aleksandr Chuklin;Pavel Serdyukov;Maarten de Rijke

  • Modeling documents as mixtures of persons for expert finding

    Pavel Serdyukov;Djoerd Hiemstra

  • Personalized Landmark Recommendation Based on Geotags from Photo Sharing Sites

    Yue Shi;Pavel Serdyukov;Alan Hanjalic;Martha A. Larson

  • Overview of the TREC 2011 Entity Track.

    Krisztian Balog;Pavel Serdyukov;Arjen P. de Vries

  • Entity ranking using Wikipedia as a pivot

    Rianne Kaptein;Pavel Serdyukov;Arjen De Vries;Jaap Kamps

  • Search for expertise: going beyond direct evidence

    Pavel Serdyukov

  • Structured Document Retrieval, Multimedia Retrieval, and Entity Ranking Using PF/Tijah

    Theodora Tsikrika;Pavel Serdyukov;Henning Rode;Thijs Westerveld

  • Working Notes for the Placing Task at MediaEval 2011

    Adam Rae;Vanessa Murdock;Pavel Serdyukov;Pascal Kelm

  • Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments

    Alexey Poyarkov;Alexey Drutsa;Andrey Khalyavin;Gleb Gusev

  • Web-based Startup Success Prediction

    Boris Sharchilev;Michael Roizner;Andrey Rumyantsev;Denis Ozornin

  • Future User Engagement Prediction and Its Application to Improve the Sensitivity of Online Experiments

    Alexey Drutsa;Gleb Gusev;Pavel Serdyukov

  • User model-based metrics for offline query suggestion evaluation

    Eugene Kharitonov;Craig Macdonald;Pavel Serdyukov;Iadh Ounis

  • An analysis of queries intended to search information for children

    Sergio Duarte Torres;Djoerd Hiemstra;Pavel Serdyukov

  • Finding Influential Training Samples for Gradient Boosted Decision Trees

    Boris Sharchilev;Yury Ustinovsky;Pavel Serdyukov;Maarten de Rijke

Frequent Co-Authors

Djoerd Hiemstra
Djoerd Hiemstra Radboud University
Maarten de Rijke
Maarten de Rijke University of Amsterdam
Arjen P. de Vries
Arjen P. de Vries Radboud University
Craig Macdonald
Craig Macdonald University of Glasgow
Iadh Ounis
Iadh Ounis University of Glasgow
Martha Larson
Martha Larson Radboud University
Krisztian Balog
Krisztian Balog University of Stavanger
Jaap Kamps
Jaap Kamps University of Amsterdam
Vanessa Murdock
Vanessa Murdock Amazon (United States)
Rico Sennrich
Rico Sennrich University of Zurich

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