research
∙
07/14/2023
Similarity-based Memory Enhanced Joint Entity and Relation Extraction
Document-level joint entity and relation extraction is a challenging inf...
share
research
∙
07/13/2023
Electoral Agitation Data Set: The Use Case of the Polish Election
The popularity of social media makes politicians use it for political ad...
research
∙
07/11/2023
Domain-Agnostic Neural Architecture for Class Incremental Continual Learning in Document Processing Platform
Production deployments in complex systems require ML architectures to be...
research
∙
06/13/2023
Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmark
Despite impressive advancements in multilingual corpora collection and m...
research
∙
03/03/2023
Graph-level representations using ensemble-based readout functions
Graph machine learning models have been successfully deployed in a varie...
research
∙
03/03/2023
RAFEN – Regularized Alignment Framework for Embeddings of Nodes
Learning representations of nodes has been a crucial area of the graph m...
research
∙
11/27/2022
Neural Architecture for Online Ensemble Continual Learning
Continual learning with an increasing number of classes is a challenging...
research
∙
11/23/2022
This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish
The availability of compute and data to train larger and larger language...
research
∙
04/11/2022
Assessment of Massively Multilingual Sentiment Classifiers
Models are increasing in size and complexity in the hunt for SOTA. But w...
research
∙
01/28/2022
Dynamic pricing and discounts by means of interactive presentation systems in stationary point of sales
The main purpose of this article was to create a model and simulate the ...
research
∙
10/11/2021
Spatial Data Mining of Public Transport Incidents reported in Social Media
Public transport agencies use social media as an essential tool for comm...
research
∙
06/04/2021
Graph Barlow Twins: A self-supervised representation learning framework for graphs
The self-supervised learning (SSL) paradigm is an essential exploration ...
research
∙
12/29/2020
AttrE2vec: Unsupervised Attributed Edge Representation Learning
Representation learning has overcome the often arduous and manual featur...
research
∙
06/17/2020
Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections
Political campaigns are full of political ads posted by candidates on so...
research
∙
06/16/2020
UCSG-Net – Unsupervised Discovering of Constructive Solid Geometry Tree
Signed distance field (SDF) is a prominent implicit representation of 3D...
research
∙
09/11/2019
Comprehensive Analysis of Aspect Term Extraction Methods using Various Text Embeddings
Recently, a variety of model designs and methods have blossomed in the c...
research
∙
09/04/2019
Extracting Aspects Hierarchies using Rhetorical Structure Theory
We propose a novel approach to generate aspect hierarchies that proved t...
research
∙
09/03/2019
Aspect Detection using Word and Char Embeddings with (Bi)LSTM and CRF
We proposed a new accurate aspect extraction method that makes use of bo...
research
∙
04/06/2019
Incremental embedding for temporal networks
Prediction over edges and nodes in graphs requires appropriate and effic...
research
∙
12/07/2018
LNEMLC: Label Network Embeddings for Multi-Label Classification
Multi-label classification aims to classify instances with discrete non-...
research
∙
12/07/2018
LNEMLC: Label Network Embeddings for Multi-Label Classifiation
Multi-label classification aims to classify instances with discrete non-...
research
∙
09/13/2017
Method for Aspect-Based Sentiment Annotation Using Rhetorical Analysis
This paper fills a gap in aspect-based sentiment analysis and aims to pr...
research
∙
04/27/2017
A Network Perspective on Stratification of Multi-Label Data
In the recent years, we have witnessed the development of multi-label cl...
research
∙
02/13/2017
Is a Data-Driven Approach still Better than Random Choice with Naive Bayes classifiers?
We study the performance of data-driven, a priori and random approaches ...
research
∙
02/05/2017
A scikit-based Python environment for performing multi-label classification
Scikit-multilearn is a Python library for performing multi-label classif...
research
∙
06/10/2016
WordNet2Vec: Corpora Agnostic Word Vectorization Method
A complex nature of big data resources demands new methods for structuri...
research
∙
06/07/2016
How is a data-driven approach better than random choice in label space division for multi-label classification?
We propose using five data-driven community detection approaches from so...
research
∙
10/05/2015