Text Mining and Analytics(1)

Coursera上的视频做笔记学习

前言:
其实,semantic network与text mining是紧密相关的。
Semantic network
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1、so this means the data mining problem is basically taking a lot of data as input and giving actionale knowledge as output
2、在data mining 内部,又有针对不同data类型的mining

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The main goal of test mining is actually to revert this process of generating text data

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the context can provide intersting angles for analyzing text data
For example, we might partion text data into different time periods
because of the availability of the time.Now we can analyze text data in each time period and then make a comparison.
Similarly we can partion text data based on locations or any meta data that’s associated to form interesting comparisons in areas.
So in this sense, non-text data can actually provide interesting angles or perspectives for text data analysis.And it can help us make context-sensitive
analysis of content or the language usage or the opinions about the observer or the authors of text data.We could analyze the sentiment in different contexts

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转载自blog.csdn.net/normol/article/details/79203254