Семантические лексиконы

material ID: semanticlexicons

Related Papers

Semi-Automatic Recognition of Noun Modifier Relationships

Authors: nan

Publication: TIPSTER (1998)

DOI: nan

Semantic relationships among words and phrases are often marked by explicit syntactic or lexical clues that help recognize such rela~ tionships in texts. Within complex nominals, however, few overt clues …...

6960

Automatic construction of a hypernym-labeled noun hierarchy from text

Authors: nan

Publication: TIPSTER (1999)

DOI: nan

Previous work has shown that automatic methods can be used in building semantic lexicons. This work goes a step further by automatically creating not just clusters of related words, but …...

35153

A Bootstrapping Method for Learning Semantic Lexicons using Extraction Pattern Contexts

Authors: nan

Publication: TIPSTER (2002)

DOI: nan

This paper describes a bootstrapping al- gorithm called Basilisk that learns high- quality semantic lexicons for multiple cate- gories. Basilisk begins with an unannotated corpus and seed words for each …...

43186

Extracting Lexico-conceptual Knowledge for Developing Persian WordNet

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

AbstractSemantic lexicons and lexical ontologies are some major resources in natural language processing. Developing such resources are time consuming tasks for which some automatic methods are proposed. This paper describes …...

7683

Paraphrasing Out-of-Vocabulary Words with Word Embeddings and Semantic Lexicons for Low Resource Statistical Machine Translation

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractOut-of-vocabulary (OOV) word is a crucial problem in statistical machine translation (SMT) with low resources. OOV paraphrasing that augments the translation model for the OOV words by using the translation …...

16698

Representation Learning for Unseen Words by Bridging Subwords to Semantic Networks

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractPre-trained word embeddings are widely used in various fields. However, the coverage of pre-trained word embeddings only includes words that appeared in corpora where pre-trained embeddings are learned. It means …...

14339