Summary of the paper
| Title | Generating a Resource for Products and Brandnames Recognition. Application to the Cosmetic Domain. |
|---|---|
| Authors | Cédric Lopez, Frédérique Segond, Olivier Hondermarck, Paolo Curtoni and Luca Dini |
| Abstract | Named Entity Recognition task needs high-quality and large-scale resources. In this paper, we present RENCO, a based-rules system focused on the recognition of entities in the Cosmetic domain (brandnames, product names, …). RENCO has two main objectives: 1) Generating resources for named entity recognition; 2) Mining new named entities relying on the previous generated resources. In order to build lexical resources for the cosmetic domain, we propose a system based on local lexico-syntactic rules complemented by a learning module. As the outcome of the system, we generate both a simple lexicon and a structured lexicon. Results of the evaluation show that even if RENCO outperforms a classic Conditional Random Fields algorithm, both systems should combine their respective strengths. |
| Topics | Lexicon, Lexical Database, Information Extraction, Information Retrieval |
Full paper  |
Generating a Resource for Products and Brandnames Recognition. Application to the Cosmetic Domain. |
| Bibtex | @InProceedings{LOPEZ14.549, author = {Cédric Lopez and Frédérique Segond and Olivier Hondermarck and Paolo Curtoni and Luca Dini}, title = {Generating a Resource for Products and Brandnames Recognition. Application to the Cosmetic Domain.}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |