Ensemble Method

The success of supervised learning approaches to word sense disambiguation is largely de- pendent on the features used to represent the context in which an ambiguous word occurs. Previous work …...

Our group participated in the Basque and En- glish lexical sample tasks in Senseval-3. language-specific feature set was defined forA Basque. Four different learning algorithms were applied, and also a …...

We describe a two-stage optimization of the MaltParser system for the ten languages in the multilingual track of the CoNLL 2007 shared task on dependency parsing. The first stage consists …...

Current approaches to the prediction of associations rely on just one type of in- formation, generally taking the form of either word space models or collocation measures. At the moment, …...

This paper describes the system implemented by Fundaci´o Barcelona Media (FBM) for clas- sifying the polarity of opinion expressions in tweets and SMSs, and which is supported by a UIMA …...

We propose an algorithm that combines su- pervised and unsupervised methods to ensem- ble multiple systems for two popular Knowl- edge Base Population (KBP) tasks, Cold Start Slot Filling (CSSF) …...

We present the IUCL system, based on super- vised learning, for the shared task on stance detection. Our official submission, the ran- dom forest model, reaches a score of 63.60, …...

AbstractRecently, neural twitter sentiment classification has become one of state-of-thearts, which relies less feature engineering work compared with traditional methods. In this paper, we propose a simple and effective ensemble …...

AbstractTo comprehend an argument and fill the gap between claims and reasons, it is vital to find the implicit supporting warrants behind. In this paper, we propose a hierarchical attention …...

Hate speech has become a major issue that is currently a hot topic in the domain of social media. Simultaneously, current proposed methods to address the issue raise concerns about …...

AbstractWe study the problem of analyzing tweets with universal dependencies (UD). We extend the UD guidelines to cover special constructions in tweets that affect tokenization, part-of-speech tagging, and labeled dependencies. …...

AbstractNeural models have become one of the most important approaches to dialog response generation. However, they still tend to generate the most common and generic responses in the corpus all …...

AbstractIn visual media, text emphasis is the strengthening of words in a text to convey the intent of the author. Text emphasis in visual media is generally done by using …...

AbstractIn this paper, we introduce a state-of-the-art pseudo-labeling technique for few-shot intent detection. We devise a folding/unfolding hierarchical clustering algorithm which assigns weighted pseudo-labels to unlabeled user utterances. We show …...

AbstractThis paper describes Tencent Neural Machine Translation systems for the WMT 2020 news translation tasks. We participate in the shared news translation task on English ↔ Chinese and English → …...

AbstractThe SemEval 2021 task 5: Toxic Spans Detection is a task of identifying considered-toxic spans in text, which provides a valuable, automatic tool for moderating online contents. This paper represents …...

AbstractWe present a qualitative analysis of the (potentially erroneous) outputs of contextualized embedding-based methods for detecting diachronic semantic change. First, we introduce an ensemble method outperforming previously described contextualized approaches. …...

AbstractThis paper presents a study on the effectiveness of various approaches for addressing the challenge of multilingual sentiment analysis in low-resource African languages. . The approaches evaluated in the study …...