Automatic extraction of synonyms and/or semantically related words has various applications in Natural Language Processing (NLP). There are currently two mainstream extraction paradigms, namely, lexicon-based and distributional approaches. The former usually suffers from low coverage, while the latter is only able to capture general relatedness rather than strict synonymy. In this paper, two ru...

Recently a large number of easily accessible information resources have become available. To increase search quality, document creation time can be taken into account in order to increase precision, and query expansion of named entities can be employed in order to increase recall. A peculiarity of named entities compared to other vocabulary terms is that they are very dynamic in appearance, and...

We extend a lexical knowledge-base of near-synonym differences with knowledge about their collocational behaviour. This type of knowledge is useful in the process of lexical choice between near-synonyms. We acquire collocations for the near-synonyms of interest from a corpus (only collocations with the appropriate sense and part-of-speech). For each word that collocates with a nearsynonym we us...

The paper addressed the question how the paraphrasing of synonyms can be linked with a fine-gained ontology based data representation. Our challenge is to identify for a set of synonyms (including terms and multiword expressions) the best lexical paraphrases suitable for given contexts. Our hypothesis is that: i. the minimal context in which the paraphrasing can be validated is different for di...

Current synonym extraction methods work in a “closed” way. Given the problem word and set of target words, researchers have to choose words synonymous with the problem word using features such as lexical patterns and distributional similarities. This paper tries to discover synonyms in an “open” way and presents a synonym extraction framework based on self-supervised learning. We first analysis...

Auto-completion is one of the most prominent features of modern information systems. The existing solutions of auto-completion provide the suggestions based on the beginning of the currently input character sequence (i.e. prefix). However, in many real applications, one entity often has synonyms or abbreviations. For example, “DBMS” is an abbreviation of “Database Management Systems”. In this p...

Corpus linguistics and its relationship with modern lexicography are paid more and more attention by linguists and lexicographers in recent years. This paper, based on corpus analysis, mainly studies EFL (English as Foreign Language) learners’ synonymous errors (SE), which refer to errors made by learners when using synonyms in writing. The unit observed is a pair of commonly used synonyms glad...