activity
20162018
most citedNeural-based Noise Filtering from Word Embeddings

3 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2018

Introducing two Vietnamese Datasets for Evaluating Semantic Models of (Dis-)Similarity and Relatedness

Kim Anh Nguyen, Sabine Schulte im Walde, Ngoc Thang Vu

We present two novel datasets for the low-resource language Vietnamese to assess models of semantic similarity: ViCon comprises pairs of synonyms and antonyms across word classes,…

cs.CL2017

Hierarchical Embeddings for Hypernymy Detection and Directionality

Kim Anh Nguyen, Maximilian Köper, Sabine Schulte im Walde +1

We present a novel neural model HyperVec to learn hierarchical embeddings for hypernymy detection and directionality. While previous embeddings have shown limitations on prototypic…

cs.CL2017★ 1 cited

Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network

Kim Anh Nguyen, Sabine Schulte im Walde, Ngoc Thang Vu

Distinguishing between antonyms and synonyms is a key task to achieve high performance in NLP systems. While they are notoriously difficult to distinguish by distributional co-occu…

cs.CL2016★ 3 cited

Neural-based Noise Filtering from Word Embeddings

Kim Anh Nguyen, Sabine Schulte im Walde, Ngoc Thang Vu

Word embeddings have been demonstrated to benefit NLP tasks impressively. Yet, there is room for improvement in the vector representations, because current word embeddings typicall…

cs.CL2016

Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction

Kim Anh Nguyen, Sabine Schulte im Walde, Ngoc Thang Vu

We propose a novel vector representation that integrates lexical contrast into distributional vectors and strengthens the most salient features for determining degrees of word simi…