Эталонный набор данных

We present a novel almost-unsupervised approach to the task of Word Sense Dis- ambiguation (WSD). We build sense ex- amples automatically, using large quanti- ties of Chinese text, and English-Chinese …...

AbstractThe overall goal of this project is to evaluate the performance of word sense alignment (WSA) systems, focusing on obtaining examples appropriate to language learners. Building a gold standard dataset …...

AbstractIdentifying cognates is an interesting task with applications in numerous research areas, such as historical and comparative linguistics, language acquisition, cross-lingual information retrieval, readability and machine translation. We propose a …...

AbstractThe NLP researcher or application-builder often wonders “what corpus should I use, or should I build one of my own? If I build one of my own, how will I …...

AbstractSentiment analysis is genre and domain dependent, i.e. the same method performs differently when applied to text that originates from different genres and domains. Intuitively, this is due to different …...

Consumers’ purchase decisions are in- creasingly influenced by user-generated online reviews. Accordingly, there has been growing concern about the poten- tial for posting deceptive opinion spam— fictitious reviews that have …...

AbstractSentiment analysis is the computational task of extracting sentiment from a text document – for example whether it expresses a positive, negative or neutral opinion. Various approaches have been introduced …...

AbstractVariations of word associations across different groups of people can provide insights into people’s psychologies and their world views. To capture these variations, we introduce the task of demographic-aware word …...

AbstractMetaphor comprehension and understanding is a complex cognitive task that requires interpreting metaphors by grasping the interaction between the meaning of their target and source concepts. This is very challenging …...

AbstractAbbreviations present a significant challenge for NLP systems because they cause tokenization and out-of-vocabulary errors. They can also make the text less readable, especially in reference printed books, where they …...

Abstract“In recent years, many researchers have recognized the importance of associating events withsentiments. Previous approaches focus on generalizing events and extracting sentimental in-formation from a large-scale corpus. However, since context …...