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Found 10 papers, 4 papers with code
Recency Ranking by Diversification of Result Set
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 degree proportional to the probability of the need in recent content.
Sequence Modeling with Unconstrained Generation Order
The dominant approach to sequence generation is to produce a sequence in some predefined order, e. g. left to right.
Latent Distribution Assumption for Unbiased and Consistent Consensus Modelling
We study the problem of aggregation noisy labels.
Context-Aware Neural Machine Translation Learns Anaphora Resolution
Standard machine translation systems process sentences in isolation and hence ignore extra-sentential information, even though extended context can both prevent mistakes in ambiguous cases and improve translation coherence.
Finding Influential Training Samples for Gradient Boosted Decision Trees
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 (GBDT).
Riemannian Optimization for Skip-Gram Negative Sampling
Skip-Gram Negative Sampling (SGNS) word embedding model, well known by its implementation in "word2vec" software, is usually optimized by stochastic gradient descent.
User Model-Based Intent-Aware Metrics for Multilingual Search Evaluation
We develop a novel approach to build intent-aware user behavior models, which overcome these limitations and convert to quality metrics that better correlate with standard online metrics of user satisfaction.
Efficient High-Order Interaction-Aware Feature Selection Based on Conditional Mutual Information
This study introduces a novel feature selection approach CMICOT, which is a further evolution of filter methods with sequential forward selection (SFS) whose scoring functions are based on conditional mutual information (MI).
Prediction of Video Popularity in the Absence of Reliable Data from Video Hosting Services: Utility of Traces Left by Users on the Web
We investigate video popularity prediction based on features from three primary sources available for a typical operating company: first, the content hosting provider may deliver its data via its API, second, the operating company makes use of its own search and browsing logs, third, the company crawls information about embeds of a video and links to a video page from publicly available resources on the Web.
Efficient Rectangular Maximal-Volume Algorithm for Rating Elicitation in Collaborative Filtering
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 item.
