activity
20172019
most citedUnibucKernel Reloaded: First Place in Arabic Dialect Identification for the Second Year in a Row

25 citations · 28 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CL2019★ 3 cited

Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation

Radu Tudor Ionescu, Andrei M. Butnaru

In this paper, we propose a novel representation for text documents based on aggregating word embedding vectors into document embeddings. Our approach is inspired by the Vector of…

cs.CL2019

MOROCO: The Moldavian and Romanian Dialectal Corpus

Andrei M. Butnaru, Radu Tudor Ionescu

In this work, we introduce the MOldavian and ROmanian Dialectal COrpus (MOROCO), which is freely available for download at https://github.com/butnaruandrei/MOROCO. The corpus conta…

cs.CL2018

Transductive Learning with String Kernels for Cross-Domain Text Classification

Radu Tudor Ionescu, Andrei M. Butnaru

For many text classification tasks, there is a major problem posed by the lack of labeled data in a target domain. Although classifiers for a target domain can be trained on labele…

cs.CL2018

Improving the results of string kernels in sentiment analysis and Arabic dialect identification by adapting them to your test set

Radu Tudor Ionescu, Andrei M. Butnaru

Recently, string kernels have obtained state-of-the-art results in various text classification tasks such as Arabic dialect identification or native language identification. In thi…

cs.CL2018★ 25 cited

UnibucKernel Reloaded: First Place in Arabic Dialect Identification for the Second Year in a Row

Andrei M. Butnaru, Radu Tudor Ionescu

We present a machine learning approach that ranked on the first place in the Arabic Dialect Identification (ADI) Closed Shared Tasks of the 2018 VarDial Evaluation Campaign. The pr…

cs.CL2018

Automated essay scoring with string kernels and word embeddings

Mădălina Cozma, Andrei M. Butnaru, Radu Tudor Ionescu

In this work, we present an approach based on combining string kernels and word embeddings for automatic essay scoring. String kernels capture the similarity among strings based on…

cs.CL2018

UnibucKernel: A kernel-based learning method for complex word identification

Andrei M. Butnaru, Radu Tudor Ionescu

In this paper, we present a kernel-based learning approach for the 2018 Complex Word Identification (CWI) Shared Task. Our approach is based on combining multiple low-level feature…

cs.CL2017

From Image to Text Classification: A Novel Approach based on Clustering Word Embeddings

Andrei M. Butnaru, Radu Tudor Ionescu

In this paper, we propose a novel approach for text classification based on clustering word embeddings, inspired by the bag of visual words model, which is widely used in computer…

cs.CL2017

ShotgunWSD: An unsupervised algorithm for global word sense disambiguation inspired by DNA sequencing

Andrei M. Butnaru, Radu Tudor Ionescu, Florentina Hristea

In this paper, we present a novel unsupervised algorithm for word sense disambiguation (WSD) at the document level. Our algorithm is inspired by a widely-used approach in the field…