Recent work has addressed opinion inferences that arise when opinions are expressed
toward+/-effect events, events that positively or negatively affect entities. Many words have …

Word sense disambiguation (WSD) is an important research topic in natural language
processing, which is widely applied to text classification, machine translation, and …

Word sense disambiguation (WSD) is one of key problems in field of natural language
processing. Ambiguous word often has different meanings in different contexts. WSD is the …

Acronym Disambiguation (AD) task aims to map the acronym in sentences to the
corresponding expansion among candidate expansions. However, these models based on …

Subjectivity restriction gradience of word senses has been a controversial and hard issue in
linguistic studies. Finding out how different syntactic and semantic features affect the senses …

To solve the problem of a word having multiple meanings in the natural language
processing (NLP) field, a semi-supervised disambiguation method, that uses a range of …

Word sense disambiguation (WSD) is important for natural language processing. It plays
important roles in information retrieval, machine translation, text categorization and topic …

Word sense disambiguation is important to machine translation. In this paper, a new word
sense classifier is proposed, whose discriminative features are extracted from parsing tree …

Recently, work in NLP was initiated on a type of opinion inference that arises when opinions
are expressed toward events which have positive or negative effects on entities, called+ …

Word sense disambiguation is important to machine translation. In this paper, a new word
sense classifier is proposed, whose discriminative features are extracted from parsing tree …