英文字典中文字典


英文字典中文字典51ZiDian.com



中文字典辞典   英文字典 a   b   c   d   e   f   g   h   i   j   k   l   m   n   o   p   q   r   s   t   u   v   w   x   y   z       







请输入英文单字，中文词皆可：


请选择你想看的字典辞典：
单词字典翻译
ner查看　ner　在百度字典中的解释百度英翻中〔查看〕
ner查看　ner　在Google字典中的解释Google英翻中〔查看〕
ner查看　ner　在Yahoo字典中的解释Yahoo英翻中〔查看〕

安装中文字典英文字典查询工具!


中文字典英文字典工具:
选择颜色:
输入中英文单字

































































英文字典中文字典相关资料:


  • Named-entity recognition - Wikipedia
    Named-entity recognition (NER) (also known as (named) entity identification, entity chunking, and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names (PER), organizations (ORG), locations (LOC), geopolitical
  • Named Entity Recognition - GeeksforGeeks
    Named Entity Recognition (NER) in NLP focuses on identifying and categorizing important information known as entities in text These entities can be names of people, places, organizations, dates, etc
  • What Is Named Entity Recognition? - IBM
    Named entity recognition (NER)—also called entity chunking or entity extraction—is a component of natural language processing (NLP) that identifies predefined categories of objects in a body of text
  • What is Named Entity Recognition (NER) in Azure AI Language?
    Named Entity Recognition (NER) is one of the features offered by Azure AI Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language The NER feature can identify and categorize entities in unstructured text
  • What is Named Entity Recognition (NER)? Methods, Use Cases . . .
    Named Entity Recognition (NER) is a sub-task of information extraction in Natural Language Processing (NLP) that classifies named entities into predefined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, and more
  • What Is Named Entity Recognition (NER) and How Does It Work?
    Named entity recognition (NER) is a natural language processing (NLP) method, which is a subcategory of artificial intelligence (AI) and machine learning (ML) Although it isn’t exactly a household name, named entity recognition powers much of the technology we use every day
  • Named Entity Recognition (NER) - Papers With Code
    Named Entity Recognition (NER) is a task of Natural Language Processing (NLP) that involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, and others
  • A Comprehensive Guide to Named Entity Recognition (NER) - Turing
    Named entity recognition (NER) is a form of natural language processing (NLP) that involves extracting and identifying essential information from text The information that is extracted and categorized is called entity
  • What Is Named Entity Recognition (NER) and How It Works?
    Named entity recognition (NER) is a subfield of natural language processing (NLP) that focuses on identifying and classifying specific data points from textual content NER works with salient details of the text, known as named entities — single words, phrases, or sequences of words — by identifying and categorizing them into predefined groups
  • Named Entity Recognition - Meaning, Example, Benefits
    Named Entities Recognition (NER) is an NLP system that helps in processing all kinds of data into proper text and then putting them under designated categories The different types of NER systems include Rule-based, Dictionary-based, machine learning-based, and hybrid forms





中文字典-英文字典  2005-2009