Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Cooking up referring expressions
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Practical very large scale CRFs
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Improving term extraction with terminological resources
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Extraction of procedural knowledge from the web: a comparison of two workflow extraction approaches
Proceedings of the 21st international conference companion on World Wide Web
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Nutrition and diet have direct and considerable impact on our well-being and health. This field attracts researchers from different areas, such as medicine, nutrition and epidemiology, computer sciences, artificial intelligence and natural language processing (NLP).We process the recipes with NLP methods in order to automatically identify ingredient names within recipes. We propose a hybrid system based on linguistic enrichment of the recipes and selection of the relevant ingredient names with a CRF method. Semantic resources have been specifically built for processing two kinds of information: exact (e.g. quantity expressed in grams or liters, durations expressed in minutes or days) and fuzzy (e.g. quantities expressed in chouilla (smidgeon) and louche (ladle), durations sequenced with aprèes, ensuite, alors que (the, after that, while)). The experiments are performed with French-language textual data. The results demonstrate that the proposed method is useful for searching and managing the recipes.