Papers by Andrei Butnaru

3 papers
Automated essay scoring with string kernels and word embeddings (P18-2)

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Challenge: Existing approaches to automatic essay scoring use low-level character n-gram features.
Approach: They propose to combine string kernels and word embeddings for automatic essay scoring.
Outcome: The proposed method outperforms state-of-the-art deep learning methods in Arabic dialect identification and native language identification tasks.
Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation (N19-1)

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Challenge: a novel word embedding representation for text documents is proposed . the method is based on the Vector of Locally-Aggregated Descriptors used for image representation .
Approach: They propose a novel representation for text documents based on aggregating word embedding vectors into document embeddables.
Outcome: The proposed representation improves on the Movie Review data set and is 10% better than the state-of-the-art representation.
MOROCO: The Moldavian and Romanian Dialectal Corpus (P19-1)

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Challenge: Using the MOldavian and ROmanian Dialectal COrpus, we perform empirical studies on dialect identification tasks.
Approach: They introduce the MOldavian and ROmanian Dialectal COrpus corpus which contains 33564 samples of text collected from the news domain.
Outcome: The proposed model is based on a shallow and deep approach to discriminate between two different languages.

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