Word, Sense, and Graph Embeddings

2020 ◽  
pp. 7-15
Author(s):  
Jose Manuel Gomez-Perez ◽  
Ronald Denaux ◽  
Andres Garcia-Silva
Keyword(s):  
Graph Embeddings ◽  
Word Sense

ConnotationWordNet: Learning Connotation over the Word+Sense Network

2014 ◽  
Author(s):  
Jun Seok Kang ◽  
Song Feng ◽  
Leman Akoglu ◽  
Yejin Choi
Keyword(s):  
Word Sense

Graph Based Word Sense Disambiguation Method Using Distance Between Words

2012 ◽  
Vol 23 (4) ◽  
pp. 776-785 ◽  
Author(s):  
Zhi-Zhuo YANG ◽  
He-Yan HUANG
Keyword(s):  
Word Sense Disambiguation ◽  
Word Sense ◽  
Sense Disambiguation

scholarly journals Graph Embeddings for Abusive Language Detection

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Noé Cécillon ◽  
Vincent Labatut ◽  
Richard Dufour ◽  
Georges Linarès
Keyword(s):  
Graph Embeddings ◽  
Language Detection

Group-wise Hub Identification by Learning Common Graph Embeddings on Grassmannian Manifold

2021 ◽  
pp. 1-1
Author(s):  
Defu Yang ◽  
Jiazhou Chen ◽  
Chenggang Yan ◽  
Minjeong Kim ◽  
Paul J. Laurienti ◽  
...  
Keyword(s):  
Graph Embeddings ◽  
Grassmannian Manifold

Developing the Persian Wordnet of Verbs Using Supervised Learning

2021 ◽  
Vol 20 (4) ◽  
pp. 1-18
Author(s):  
Zahra Mousavi ◽  
Heshaam Faili
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Language Processing ◽  
Supervised Classification ◽  
Word Sense ◽  
Direct Influence ◽  
Training Set ◽  
Bilingual Dictionary ◽  
Automated Method ◽  
Princeton Wordnet

Nowadays, wordnets are extensively used as a major resource in natural language processing and information retrieval tasks. Therefore, the accuracy of wordnets has a direct influence on the performance of the involved applications. This paper presents a fully-automated method for extending a previously developed Persian wordnet to cover more comprehensive and accurate verbal entries. At first, by using a bilingual dictionary, some Persian verbs are linked to Princeton WordNet synsets. A feature set related to the semantic behavior of compound verbs as the majority of Persian verbs is proposed. This feature set is employed in a supervised classification system to select the proper links for inclusion in the wordnet. We also benefit from a pre-existing Persian wordnet, FarsNet, and a similarity-based method to produce a training set. This is the largest automatically developed Persian wordnet with more than 27,000 words, 28,000 PWN synsets and 67,000 word-sense pairs that substantially outperforms the previous Persian wordnet with about 16,000 words, 22,000 PWN synsets and 38,000 word-sense pairs.

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