UWB at SemEval-2018 Task 10: Capturing Discriminative Attributes from Word Distributions

no code implementations • SEMEVAL 2018 • Tom{\'a}{\v{s}} Brychc{\'\i}n, Tom{\'a}{\v{s}} Hercig, Josef Steinberger, Michal Konkol

We show the word distribution in the corpus has potential for detecting discriminative attributes.

Attribute Relation Extraction

Geographical Evaluation of Word Embeddings

no code implementations • IJCNLP 2017 • Michal Konkol, Tom{\'a}{\v{s}} Brychc{\'\i}n, Michal Nykl, Tom{\'a}{\v{s}} Hercig

We implement this principle by comparing the information in the word embeddings with geographical positions of cities.

Machine Translation Named Entity Recognition (NER) +3

Cross-lingual Flames Detection in News Discussions

no code implementations • RANLP 2017 • Josef Steinberger, Tom{\'a}{\v{s}} Brychc{\'\i}n, Tom{\'a}{\v{s}} Hercig, Peter Krejzl

We introduce Flames Detector, an online system for measuring flames, i. e. strong negative feelings or emotions, insults or other verbal offences, in news commentaries across five languages.

Sarcasm Detection Sentiment Analysis +1

Pyramid-based Summary Evaluation Using Abstract Meaning Representation

no code implementations • RANLP 2017 • Josef Steinberger, Peter Krejzl, Tom{\'a}{\v{s}} Brychc{\'\i}n

We propose a novel metric for evaluating summary content coverage.

Graph Similarity Sentence

Unsupervised Dialogue Act Induction using Gaussian Mixtures

no code implementations • EACL 2017 • Tom{\'a}{\v{s}} Brychc{\'\i}n, Pavel Kr{\'a}l

This paper introduces a new unsupervised approach for dialogue act induction.

Topic Models

Latent Tree Language Model

1 code implementation • EMNLP 2016 • Tom{\'a}{\v{s}} Brychc{\'\i}n

Automatic Speech Recognition (ASR) Language Modelling +2

UWB at SemEval-2016 Task 2: Interpretable Semantic Textual Similarity with Distributional Semantics for Chunks

no code implementations • SEMEVAL 2016 • Miloslav Konop{\'\i}k, Ond{\v{r}}ej Pra{\v{z}}{\'a}k, David Steinberger, Tom{\'a}{\v{s}} Brychc{\'\i}n

Semantic Textual Similarity Task 2 +1

UWB at SemEval-2016 Task 5: Aspect Based Sentiment Analysis

no code implementations • SEMEVAL 2016 • Tom{\'a}{\v{s}} Hercig, Tom{\'a}{\v{s}} Brychc{\'\i}n, Luk{\'a}{\v{s}} Svoboda, Michal Konkol

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)

UWB at SemEval-2016 Task 1: Semantic Textual Similarity using Lexical, Syntactic, and Semantic Information

no code implementations • SEMEVAL 2016 • Tom{\'a}{\v{s}} Brychc{\'\i}n, Luk{\'a}{\v{s}} Svoboda

Semantic Textual Similarity

UWB: Machine Learning Approach to Aspect-Based Sentiment Analysis

no code implementations • SEMEVAL 2014 • Tom{\'a}{\v{s}} Brychc{\'\i}n, Michal Konkol, Josef Steinberger

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2

Aspect-Level Sentiment Analysis in Czech

no code implementations • WS 2014 • Josef Steinberger, Tom{\'a}{\v{s}} Brychc{\'\i}n, Michal Konkol

Sentiment Analysis

Unsupervised Improving of Sentiment Analysis Using Global Target Context

no code implementations • RANLP 2013 • Tom{\'a}{\v{s}} Brychc{\'\i}n, Ivan Habernal

Sentiment Analysis