- Language
-
Englisch
- Identifier
-
1178422437
Subject
Computerlinguistik; Natürliche Sprache; Information Extraction; Lebensmittel; Korpus
Contributor
Wiegand, Michael
Klakow, Dietrich
Association for Computational Linguistics
Klakow, Dietrich
Association for Computational Linguistics
- URN
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
26.01.2023, 1:55 PM CET
Object type
- Monografie
Associated
- Wiegand, Michael
- Klakow, Dietrich
- Association for Computational Linguistics
Other Objects (12)
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Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Generalization Methods for In-Domain and Cross-Domain Opinion Holder Extraction
Convolution Kernels for Opinion Holder Extraction
The Role of Predicates in Opinion Holder Extraction
Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction
Data-driven Knowledge Extraction for the Food Domain
Predicate Acquisition for Opinion Holder Extraction : A Data-Intensive Approach
Towards the Detection of Reliable Food-Health Relationships
Bootstrapping polarity classifiers with rule-based classification
Towards Contextual Healthiness Classification of Food Items - A Linguistic Approach
Separating Brands from Types: an Investigation of Different Features for the Food Domain
Detecting conditional healthiness of food items from natural language text
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Generalization Methods for In-Domain and Cross-Domain Opinion Holder Extraction
Convolution Kernels for Opinion Holder Extraction
The Role of Predicates in Opinion Holder Extraction
Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction
Data-driven Knowledge Extraction for the Food Domain
Predicate Acquisition for Opinion Holder Extraction : A Data-Intensive Approach
Towards the Detection of Reliable Food-Health Relationships
Bootstrapping polarity classifiers with rule-based classification
Towards Contextual Healthiness Classification of Food Items - A Linguistic Approach
Separating Brands from Types: an Investigation of Different Features for the Food Domain
Detecting conditional healthiness of food items from natural language text
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Generalization Methods for In-Domain and Cross-Domain Opinion Holder Extraction
Convolution Kernels for Opinion Holder Extraction
The Role of Predicates in Opinion Holder Extraction
Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction
Data-driven Knowledge Extraction for the Food Domain
Predicate Acquisition for Opinion Holder Extraction : A Data-Intensive Approach
Towards the Detection of Reliable Food-Health Relationships