在线英语词典

1、Collins

http://www.collinsdictionary.com/

 

2、Merriam-Webster

 

http://www.wordcentral.com/

http://www.merriam-webster.com/

 

3、Oxford

http://www.oxforddictionaries.com/

 

4、Cambridge

http://dictionary.cambridge.org/

 

5、Longman

http://global.longmandictionaries.com/

 

6、Macmillan

http://www.macmillandictionary.com/

 

7、Heritage

https://www.ahdictionary.com/

 

8、Wordnik

https://www.wordnik.com/

 

9、Dictionary.com

http://dictionary.com

 

10、WordNet

http://wordnet.princeton.edu

 

11、Wiktionary

https://en.wiktionary.org/

 

为什么要使用不同的词典？因为不同的词典还是有一些差异，特别是英美的差异，下面对比一下不同词典对big data的解释：

 

Definition of big data in English:

 

noun

 

Oxford: Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.

 

Collins: Data held in such large amounts that it can be difficult to process.

 

Cambridge: Very large sets of data that are produced by people using the internet, and that can only be stored, understood, and used with the help of special tools and methods.

 

Macmillan: The data generated by online activity, the quantities of which are so large that new tools and methods are needed to analyse it.

 

Longman: The very large amounts of information that can now be gathered, kept, and analysed, especially information about people’s interests or what they like, as a result of things such as social media use.

 

Merriam-webster: An accumulation of data that is too large and complex for processing by traditional database management tools.

 

RandomHouse: Data sets, typically consisting of billions or trillions of records, that are so vast and complex that they require new and powerful computational resources to process.

 

Wiktionary: A collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications; its processing (capture, storage) or usage (analysis, visualization).​

 

 

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