Ảnh đại diện của raduion
Cờ của Romania Bucharest, Romania
Member since Ngày 21 tháng 01 năm 2007
0 Đề xuất


Trực tuyến Ngoại tuyến
I am a Natural Language Processing (NLP) specialist. I hold a PhD degree in this field of Artificial Intelligence (thesis subject: "Word Sense Disambiguation"). I am a good Perl programmer and I also can write C/C++/C# or Java code. I put a lot of emphasis on algorithms and their space and time requirements and I prefer to code stand-alone applications. I am a theory oriented kind of guy and not a specific technology adept (in principle I can write code in any language as long as the documentation is available).
$20 USD/giờ
3 đánh giá
  • 75%Các công việc hoàn thành
  • 100%Đúng ngân sách
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Kinh nghiệm

Senior Researcher

Aug 2001

I am a Natural Language Processing researcher. I currently work on/with: - machine translation (e.g. Moses) - part-of-speech tagging (e.g. HMMs, neural nets) - lemmatization/stemming - word sense disambiguation - parsing (syntactic analysis, dependency parsing) - question answering - word alignment - automatic bilingual dictionary extraction from parallel or comparable corpora Full resume can be found here: ~radu/

Junior C++ Programmer

Jan 2001 - Mar 2001 (2 months)

C++ programming in the company's COSWIN application.

Giáo dục

Bachelor of Engineering in Computer Science

1996 - 2001 (5 years)

Graduate Studies in Computer Science

2001 - 2002 (1 year)

Master in Theoretical Lingustics

2002 - 2003 (1 year)

PhD in Computer Science/Natural Language Processing

2003 - 2007 (4 years)

Các xuất bản

Wikipedia as an SMT Training Corpus

We have mined for parallel sentences in the Wikipedia seen as a comparable corpora. We have tested the quality of the corpus by doing SMT with Moses trained on the extracted data.

The Romanian wordnet in a nutshell

This is an account of the current development activities of the Romanian semantic network, aligned to Princeton WordNet.

Large tagset labeling using Feed Forward Neural Networks. Case study on Romanian Language

High accuracy POS tagging with neural nets, using a large tagset named Morpho-Syntactic Descriptors.

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