Search Results for author:
Found 19 papers, 1 papers with code
Transformer-based classification of user queries for medical consultancy with respect to expert specialization
This research presents an innovative strategy, utilizing the RuBERT model, for categorizing user inquiries in the field of medical consultation with a focus on expert specialization.
On Interpretability and Similarity in Concept-Based Machine Learning
We discuss how notions from cooperative game theory can be used to assess the contribution of individual attributes in classification and clustering processes in concept-based machine learning.
Triclustering in Big Data Setting
In this paper, we describe versions of triclustering algorithms adapted for efficient calculations in distributed environments with MapReduce model or parallelisation mechanism provided by modern programming languages.
Object-Attribute Biclustering for Elimination of Missing Genotypes in Ischemic Stroke Genome-Wide Data
The proposed algorithm was also able to generate biclusters for the whole dataset without size constraints in comparison to the In-Close4 algorithm for generation of formal concepts.
DaNetQA: a yes/no Question Answering Dataset for the Russian Language
The task is to take both the question and a paragraph as input and come up with a yes/no answer, i. e. to produce a binary output.
Mixed Integer Programming for Searching Maximum Quasi-Bicliques
This paper is related to the problem of finding the maximal quasi-bicliques in a bipartite graph (bigraph).
Compression of Recurrent Neural Networks for Efficient Language Modeling
We propose a general pipeline for applying the most suitable methods to compress recurrent neural networks for language modeling.
Neural Networks Compression for Language Modeling
In this paper, we consider several compression techniques for the language modeling problem based on recurrent neural networks (RNNs).
Introduction to Formal Concept Analysis and Its Applications in Information Retrieval and Related Fields
This paper is a tutorial on Formal Concept Analysis (FCA) and its applications.
Multimodal Clustering for Community Detection
Multimodal clustering is an unsupervised technique for mining interesting patterns in $n$-adic binary relations or $n$-mode networks.
Towards a Unified Taxonomy of Biclustering Methods
Being an unsupervised machine learning and data mining technique, biclustering and its multimodal extensions are becoming popular tools for analysing object-attribute data in different domains.
Bayesian Learning of Consumer Preferences for Residential Demand Response
In coming years residential consumers will face real-time electricity tariffs with energy prices varying day to day, and effective energy saving will require automation - a recommender system, which learns consumer's preferences from her actions.
Two-stage Cascaded Classifier for Purchase Prediction
In this paper we describe our machine learning solution for the RecSys Challenge, 2015.
RAPS: A Recommender Algorithm Based on Pattern Structures
We propose a new algorithm for recommender systems with numeric ratings which is based on Pattern Structures (RAPS).
Can FCA-based Recommender System Suggest a Proper Classifier?
The paper briefly introduces multiple classifier systems and describes a new algorithm, which improves classification accuracy by means of recommendation of a proper algorithm to an object classification.
Reciprocity in Gift-Exchange-Games
Since this paper uses state-of-art data science techniques, the results provide a different point of view on the problem.
A Typology of Collaboration Platform Users
In this paper we present a review of the existing typologies of Internet service users.
An FCA-based Boolean Matrix Factorisation for Collaborative Filtering
We propose a new approach for Collaborative Filtering which is based on Boolean Matrix Factorisation (BMF) and Formal Concept Analysis.
Concept Stability for Constructing Taxonomies of Web-site Users
Owners of a web-site are often interested in analysis of groups of users of their site.
