Extractive Text Summarization in Python
Motivation:
The length of textual data is increasing and people have less time. Often the newspaper articles run into a long text of, say 1000 -1200 words. As wearable devices leap to prominence (Google Glass, Apple Watch, to name a few), content must adapt to the limited screen space available on these devices. The task of generating intelligent and accurate summaries for long pieces of text has become a popular research as well as industry problem.
Approach:
Extractive text summarization is all about finding the more important sentences from a document as a summary of that document. Our approach is using the TextRank algorithm to find these 'important' sentences.
video output
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