Content Summarization
Category: Diagnostic Analytics
This technology takes in original data, usually in the form of an essay or an article, and reduces it to a much sorter content summary. "Summarization is the task of condensing a piece of text to a shorter version, reducing the size of the initial text while at the same time preserving key informational elements and the meaning of content" (Goncalves, 2020).
Content siummarization can be 'extractive', which means relatively significant sentences and phrases are extracted from the document and assembled in a sequence, or it can be 'abstractive', "by interpreting the text using advanced natural language techniques in order to generate a new shorter text — parts of which may not appear as part of the original document, that conveys the most critical information from the original text" (Goncalves, 2020).
Examples and Articles
Automatic Text Summarization with Machine Learning — An overview
LuÃs Gonçalves, Apr 11, 2020, Medium. Detailed description of content summarization with diagrams and examples.
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TL;DR: The Top 6 Text Summarization APIs
Examples provided: Aylien – Text Analysis, MeaningCloud – Summarization, ML Analyzer, Recognant Summarization Index, Summarize Text and Text Summary will give your app’s users the gist of any article in a fraction of the time it takes to read the original.
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