Linear Classifier

We consider the problem of assigning level numbers (weights) to hierarchically organized categories during text categorization. These levels control the ability of the categories to attract documents during the catego- …...

This paper describes the details of our system submitted to the SemEval-2013 shared task on sentiment analysis in Twitter. Our approach to predicting the sentiment of Tweets and SMS is …...

This paper describes our system used in the Aspect Based Sentiment Analysis Task 4 at the SemEval-2014. Our system con- sists of two components to address two of the subtasks …...

AbstractA writer’s style depends not just on personal traits but also on her intent and mental state. In this paper, we show how variants of the same writing task can …...

AbstractWe present LightRel, a lightweight and fast relation classifier. Our goal is to develop a high baseline for different relation extraction tasks. By defining only very few data-internal, word-level features …...

AbstractLuminoso participated in the SemEval 2018 task on “Capturing Discriminative Attributes” with a system based on ConceptNet, an open knowledge graph focused on general knowledge. In this paper, we describe …...

AbstractFine-tuning (FT) pre-trained sentence embedding models on small datasets has been shown to have limitations. In this paper we show that concatenating the embeddings from the pre-trained model with those …...

AbstractIn order to facilitate natural language understanding, the key is to engage commonsense or background knowledge. However, how to engage commonsense effectively in question answering systems is still under exploration …...

AbstractIn this paper, we present the system submitted to “SemEval-2020 Task 12”. The proposed system aims at automatically identify the Offensive Language in Arabic Tweets. A machine learning based approach …...

AbstractDebate transcripts from the UK Parliament contain information about the positions taken by politicians towards important topics, but are difficult for people to process manually. While sentiment analysis of debate …...

AbstractThis paper presents an empirical study to efficiently build named entity recognition (NER) systems when a small amount of in-domain labeled data is available. Based upon recent Transformer-based self-supervised pre-trained …...

Commonsense reasoning is one of the key problems in natural language processing, but the relative scarcity of labeled data holds back the progress for languages other than English. Pretrained cross-lingual …...