Search Results for author: Sergiu Nisioi

Found 13 papers, 1 papers with code

Content Extraction and Lexical Analysis from Customer-Agent Interactions

no code implementations WS 2018 Sergiu Nisioi, Anca Bucur, Liviu P. Dinu

In this paper, we provide a lexical comparative analysis of the vocabulary used by customers and agents in an Enterprise Resource Planning (ERP) environment and a potential solution to clean the data and extract relevant content for NLP.

Lexical Analysis

Exploring Neural Text Simplification Models

1 code implementation ACL 2017 Sergiu Nisioi, Sanja {\v{S}}tajner, Simone Paolo Ponzetto, Liviu P. Dinu

Unlike the previously proposed automated TS systems, our neural text simplification (NTS) systems are able to simultaneously perform lexical simplification and content reduction.

Lexical Simplification Machine Translation +2

A Visual Representation of Wittgenstein's Tractatus Logico-Philosophicus

no code implementations WS 2016 Anca Bucur, Sergiu Nisioi

In this paper we present a data visualization method together with its potential usefulness in digital humanities and philosophy of language.

Data Visualization

Vanilla Classifiers for Distinguishing between Similar Languages

no code implementations WS 2016 Sergiu Nisioi, Alina Maria Ciobanu, Liviu P. Dinu

In this paper we describe the submission of the UniBuc-NLP team for the Discriminating between Similar Languages Shared Task, DSL 2016.

Information Retrieval Language Identification +1

On the Similarities Between Native, Non-native and Translated Texts

no code implementations ACL 2016 Ella Rabinovich, Sergiu Nisioi, Noam Ordan, Shuly Wintner

We present a computational analysis of three language varieties: native, advanced non-native, and translation.

Translation

A Corpus of Native, Non-native and Translated Texts

no code implementations LREC 2016 Sergiu Nisioi, Ella Rabinovich, Liviu P. Dinu, Shuly Wintner

We describe a monolingual English corpus of original and (human) translated texts, with an accurate annotation of speaker properties, including the original language of the utterances and the speaker{'}s country of origin.

Using Word Embeddings to Translate Named Entities

no code implementations LREC 2016 Octavia-Maria {\c{S}}ulea, Sergiu Nisioi, Liviu P. Dinu

In this paper we investigate the usefulness of neural word embeddings in the process of translating Named Entities (NEs) from a resource-rich language to a language low on resources relevant to the task at hand, introducing a novel, yet simple way of obtaining bilingual word vectors.

Chinese Named Entity Recognition NER +2

Comparing Speech and Text Classification on ICNALE

no code implementations LREC 2016 Sergiu Nisioi

In this paper we explore and compare a speech and text classification approach on a corpus of native and non-native English speakers.

Classification General Classification +1

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