Семантикалық ерекшеліктер

Recently we have begun to build the basic tools for a genetic speech-dialog system. The main modules, their function and internal ccommunication have been specified. The different components ~e connected …...

AbstractMachine Translation (MT) systems that process unrestricted text should be able to deal with words that are not found in the MT lexicon. Without some kind of recognition, the parse …...

We analyze models for semantic role assignment by defining a meta-model that abstracts over features and learning paradigms. This meta-model is based on the concept of role confusability, is de- …...

Key phrases are usually among the most information-bearing linguistic structures. Translating them correctly will improve many natural language processing appli- cations. We propose a new framework to mine key phrase …...

The increasing use of large open-domain document sources is exacerbating the problem of ambiguity in named entities. This paper explores the use of a range of syntactic and semantic features …...

This short paper presents a system developed at the Université Paris 13 for the Semeval 2007 Metonymy Resolution Task (task #08, location name track; see Markert and Nissim, 2007). The …...

In previous research in automatic verb classification, syntactic features have proved the most useful features, although manual classifications rely heavily on se- mantic features. We show, in contrast with previous …...

. We introduce a method for learning to assign suitable sentiment ratings to review articles. In our approach, reviews are transformed into collections of n-gram and semantic word class features …...

AbstractElectronic dictionaries offer many possibilities unavailable in paper dictionaries to view, display or access information. However, even these resources fall short when it comes to access words sharing semantic features …...

AbstractThe task of parse disambiguation has gained in importance over the last decade as the complexity of grammars used in deep linguistic processing has been increasing. In this paper we …...

Traditional approaches to sentiment classifica- tion rely on lexical features, syntax-based fea- tures or a combination of the two. We pro- pose semantic features using word senses for a supervised …...

We investigate the task of medical concept coreference resolution in clinical text using two semi-supervised methods, co-training and multi-view learning with posterior regulariza- tion. By extracting semantic and temporal features …...

AbstractThis paper presents Walenty, a comprehensive valence dictionary of Polish, with a number of novel features, as compared to other such dictionaries. The notion of argument is based on the …...

The widespread use of deception in online sources has motivated the need for meth- ods to automatically profile and identify deceivers. This work explores deception, gender and age detection in …...

A simile is a comparison between two essentially unlike things, such as “Jane swims like a dolphin”. Similes often ex- press a positive or negative sentiment to- ward something, but …...

AbstractIn this paper, we first build a manually annotated named entity corpus of Mongolian. Then, we propose three morphological processing methods and study comprehensive features, including syllable features, lexical features, …...

AbstractTemporality is crucial in understanding the course of clinical events from a patient’s electronic health recordsand temporal processing is becoming more and more important for improving access to content. SemEval …...

AbstractWith the growth in the usage of social media, it has become increasingly common for people to hide behind a mask and abuse others. We have attempted to detect such …...

AbstractBERT is a recent language representation model that has surprisingly performed well in diverse language understanding benchmarks. This result indicates the possibility that BERT networks capture structural information about language. …...

AbstractIn this paper, we propose a new few-shot text classification method. Compared with supervised learning methods which require a large corpus of labeled documents, our method aims to make it …...

AbstractThis paper revisits feature engineering approaches for predicting the complexity level of English words in a particular context using regression techniques. Our best submission to the Lexical Complexity Prediction (LCP) …...

AbstractCurrent dialogue summarization systems usually encode the text with a number of general semantic features (e.g., keywords and topics) to gain more powerful dialogue modeling capabilities. However, these features are …...

AbstractAttention based methods for image-text generation often focus on visual features individually, while ignoring relationship information among image features that provides important guidance for generating sentences. To alleviate this issue, …...

AbstractRecognizing the layout of unstructured digital documents is crucial when parsing the documents into the structured, machine-readable format for downstream applications. Recent studies in Document Layout Analysis usually rely on …...

AbstractIn computational literary studies, the challenging task of predicting quality or reader-appreciation of narrative texts is confounded by volatile definitions of quality and the vast feature space that may be …...