Machine Learning in Natural Language Processing
نویسنده
چکیده
2 Tagging 5 2.1 PoS tagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Features for PoS Tagging . . . . . . . . . . . . . . . . 6 2.1.2 PoS Tagging Results for Different Languages . . . . . 7 2.2 Named Entity Recognition . . . . . . . . . . . . . . . . . . . . 8 2.2.1 One-step vs Two-step Classification . . . . . . . . . . 8 2.2.2 Features for NER . . . . . . . . . . . . . . . . . . . . . 9 2.2.3 ML Algorithms for NER . . . . . . . . . . . . . . . . . 10 2.2.4 Evaluation for NER . . . . . . . . . . . . . . . . . . . 10
منابع مشابه
Corpus based coreference resolution for Farsi text
"Coreference resolution" or "finding all expressions that refer to the same entity" in a text, is one of the important requirements in natural language processing. Two words are coreference when both refer to a single entity in the text or the real world. So the main task of coreference resolution systems is to identify terms that refer to a unique entity. A coreference resolution tool could be...
متن کاملA Novel Approach to Conditional Random Field-based Named Entity Recognition using Persian Specific Features
Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...
متن کاملA Hybrid Optimization Algorithm for Learning Deep Models
Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...
متن کاملA Hybrid Optimization Algorithm for Learning Deep Models
Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...
متن کاملTransparent Machine Learning Algorithm Offers Useful Prediction Method for Natural Gas Density
Machine-learning algorithms aid predictions for complex systems with multiple influencing variables. However, many neural-network related algorithms behave as black boxes in terms of revealing how the prediction of each data record is performed. This drawback limits their ability to provide detailed insights concerning the workings of the underlying system, or to relate predictions to specific ...
متن کاملCorefrence resolution with deep learning in the Persian Labnguage
Coreference resolution is an advanced issue in natural language processing. Nowadays, due to the extension of social networks, TV channels, news agencies, the Internet, etc. in human life, reading all the contents, analyzing them, and finding a relation between them require time and cost. In the present era, text analysis is performed using various natural language processing techniques, one ...
متن کامل