Improvement in Domain-Specific Named Entity Recognition by Utilizing the Real-World Data
نویسندگان
چکیده
منابع مشابه
Domain Specific Named Entity Recognition Referring to the Real World by Deep Neural Networks
In this paper, we propose a method for referring to the real world to improve named entity recognition (NER) specialized for a domain. Our method adds a stacked autoencoder to a text-based deep neural network for NER. We first train the stacked auto-encoder only from the real world information, then the entire deep neural network from sentences annotated with NEs and accompanied by real world i...
متن کاملNamed Entity Recognition in Persian Text using Deep Learning
Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...
متن کاملDomain Specific Named Entity Recognition (DSNER) from Web Documents
Named entity recognition is a tool, which use process natural language tasks such as, text categorization, speech translation, and document classification. The Web data promotes the idea, that more and more data can be interconnected. A step towards this goal is to bring more structured annotations to existing documents using common vocabularies or ontology. Semi-structured texts such as scient...
متن کاملNamed Entity Recognition for the Agricultural Domain
Agricultural data have a major role in the planning and success of rural development activities. Agriculturalists, planners, policy makers, government officials, farmers and researchers require relevant information to trigger decision making processes. This paper presents our approach towards extracting named entities from real-world agricultural data from different areas of agriculture using C...
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 کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Natural Language Processing
سال: 2017
ISSN: 1340-7619,2185-8314
DOI: 10.5715/jnlp.24.655