Monografie
Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction
- Sprache
-
Englisch
- Identifier
-
1178422453
Thema
Computerlinguistik; Korpus ; Text Mining; Maschinelles Lernen; Lebensmittel
Beteiligte Personen und Organisationen
Wiegand, Michael
Roth, Benjamin
Klakow, Dietrich
Roth, Benjamin
Klakow, Dietrich
- DOI
-
10.3115/v1/E14-1071
- URN
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
26.01.2023, 13:52 MEZ
Objekttyp
- Monografie
Beteiligte
- Wiegand, Michael
- Roth, Benjamin
- Klakow, Dietrich
Ähnliche Objekte (12)
Towards Contextual Healthiness Classification of Food Items - A Linguistic Approach
Separating Brands from Types: an Investigation of Different Features for the Food Domain
Convolution Kernels for Opinion Holder Extraction
The Role of Predicates in Opinion Holder Extraction
Generalization Methods for In-Domain and Cross-Domain Opinion Holder Extraction
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Towards the Detection of Reliable Food-Health Relationships
Predicate Acquisition for Opinion Holder Extraction : A Data-Intensive Approach
Detecting conditional healthiness of food items from natural language text
Bootstrapping polarity classifiers with rule-based classification
Data-driven Knowledge Extraction for the Food Domain
A Survey on Hate Speech Detection using Natural Language Processing
Towards Contextual Healthiness Classification of Food Items - A Linguistic Approach
Separating Brands from Types: an Investigation of Different Features for the Food Domain
Convolution Kernels for Opinion Holder Extraction
The Role of Predicates in Opinion Holder Extraction
Generalization Methods for In-Domain and Cross-Domain Opinion Holder Extraction
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Towards the Detection of Reliable Food-Health Relationships
Predicate Acquisition for Opinion Holder Extraction : A Data-Intensive Approach
Detecting conditional healthiness of food items from natural language text
Bootstrapping polarity classifiers with rule-based classification
Data-driven Knowledge Extraction for the Food Domain
A Survey on Hate Speech Detection using Natural Language Processing
Towards Contextual Healthiness Classification of Food Items - A Linguistic Approach
Separating Brands from Types: an Investigation of Different Features for the Food Domain
Convolution Kernels for Opinion Holder Extraction
The Role of Predicates in Opinion Holder Extraction
Generalization Methods for In-Domain and Cross-Domain Opinion Holder Extraction
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Towards the Detection of Reliable Food-Health Relationships
Predicate Acquisition for Opinion Holder Extraction : A Data-Intensive Approach
Detecting conditional healthiness of food items from natural language text
Bootstrapping polarity classifiers with rule-based classification
Data-driven Knowledge Extraction for the Food Domain