31 citations · 89 across the 13 of their papers we have counts for
14 papers
Recency Ranking by Diversification of Result Set
Andrey Styskin, Fedor Romanenko, Fedor Vorobyev +1
In this paper, we propose a web search retrieval approach which automatically detects recency sensitive queries and increases the freshness of the ordinary document ranking by a de…
Sequence Modeling with Unconstrained Generation Order
Dmitrii Emelianenko, Elena Voita, Pavel Serdyukov
The dominant approach to sequence generation is to produce a sequence in some predefined order, e.g. left to right. In contrast, we propose a more general model that can generate t…
Latent Distribution Assumption for Unbiased and Consistent Consensus Modelling
Valentina Fedorova, Gleb Gusev, Pavel Serdyukov
We study the problem of aggregation noisy labels. Usually, it is solved by proposing a stochastic model for the process of generating noisy labels and then estimating the model par…
Online Evaluation for Effective Web Service Development
Roman Budylin, Alexey Drutsa, Gleb Gusev +2
Development of the majority of the leading web services and software products today is generally guided by data-driven decisions based on evaluation that ensures a steady stream of…
Context-Aware Neural Machine Translation Learns Anaphora Resolution
Elena Voita, Pavel Serdyukov, Rico Sennrich +1
Standard machine translation systems process sentences in isolation and hence ignore extra-sentential information, even though extended context can both prevent mistakes in ambiguo…
Finding Influential Training Samples for Gradient Boosted Decision Trees
Boris Sharchilev, Yury Ustinovsky, Pavel Serdyukov +1
We address the problem of finding influential training samples for a particular case of tree ensemble-based models, e.g., Random Forest (RF) or Gradient Boosted Decision Trees (GBD…
Riemannian Optimization for Skip-Gram Negative Sampling
Alexander Fonarev, Oleksii Hrinchuk, Gleb Gusev +2
Skip-Gram Negative Sampling (SGNS) word embedding model, well known by its implementation in "word2vec" software, is usually optimized by stochastic gradient descent. However, the…
User Model-Based Intent-Aware Metrics for Multilingual Search Evaluation
Alexey Drutsa, Andrey Shutovich, Philipp Pushnyakov +3
Despite the growing importance of multilingual aspect of web search, no appropriate offline metrics to evaluate its quality are proposed so far. At the same time, personal language…
Prediction of Video Popularity in the Absence of Reliable Data from Video Hosting Services: Utility of Traces Left by Users on the Web
Alexey Drutsa, Gleb Gusev, Pavel Serdyukov
With the growth of user-generated content, we observe the constant rise of the number of companies, such as search engines, content aggregators, etc., that operate with tremendous…
Efficient Rectangular Maximal-Volume Algorithm for Rating Elicitation in Collaborative Filtering
Alexander Fonarev, Alexander Mikhalev, Pavel Serdyukov +2
Cold start problem in Collaborative Filtering can be solved by asking new users to rate a small seed set of representative items or by asking representative users to rate a new ite…
Intent Models for Contextualising and Diversifying Query Suggestions
Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov +1
The query suggestion or auto-completion mechanisms help users to type less while interacting with a search engine. A basic approach that ranks suggestions according to their freque…
Timely crawling of high-quality ephemeral new content
Damien Lefortier, Liudmila Ostroumova, Egor Samosvat +1
Nowadays, more and more people use the Web as their primary source of up-to-date information. In this context, fast crawling and indexing of newly created Web pages has become cruc…
Empirical Validation of the Buckley--Osthus Model for the Web Host Graph: Degree and Edge Distributions
Maxim Zhukovskiy, Dmitry Vinogradov, Yuri Pritykin +5
There has been a lot of research on random graph models for large real-world networks such as those formed by hyperlinks between web pages in the world wide web. Though largely suc…
Personalised Travel Recommendation based on Location Co-occurrence
Maarten Clements, Pavel Serdyukov, Arjen P. de Vries +1
We propose a new task of recommending touristic locations based on a user's visiting history in a geographically remote region. This can be used to plan a touristic visit to a new…