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With this type, the article summarizer will extract snippets from the whole text without changing or altering them in any way.It involves paraphrasing the parts of text you initially input into the summarizer tool.As you can see, the possibilities are endless.

With this type, the article summarizer will extract snippets from the whole text without changing or altering them in any way.

The process is very similar to extracting key phrases, where the purpose is to find phrases or individual words that could be used as tags for the text or document.

In other words, an extraction-based summary generator copies the most important information from the source text and puts the pieces together to create a summary.

Abstraction-based
This type of summary is more advanced than the extraction-based type. It involves paraphrasing the parts of text you initially input into the summarizer tool.

Generally speaking, tools that can perform this type of summarization do a much better job of condensing the source text, bringing results that are superior to those of extraction-based summarizers.

The only downside is that it’s much more difficult to develop such tools. The main reason for this is that in order to work properly, an abstraction-based summary generator requires natural language generation technology. This field is continuously growing, and there have been attempts to create an abstract synopsis capability that’s similar to what we as humans have. But for now, the majority of summary tools remain extraction-based.

Aided summarization
This type comes as the result of merging findings from the fields of machine learning, text mining, and information retrieval in an attempt to improve the process of automatic summary generation.

This is an obvious step away from fully automatic summarizers towards a slightly different concept. Instead of being a summary generator that does the entire job itself, machine-aided human summarization systems only provide help in the process. For instance, they can highlight passages that could potentially be included in a summary.

On the other hand, human-aided machine summarization systems act in a reverse manner. They generate a summary on their own so that the result can later be processed by a human.

As you can see, the possibilities are endless. It’s only a matter of further developments in the field that will bring automatic text summary creation to the next level.

But for now, a free online summarizer has already proven its usefulness.

If you’re short on time, have a ton of assignments that will take you forever to complete, or just don’t feel like sitting for hours trying to capture the main idea from a lengthy text—be sure to try a free summarizer. It’ll make writing summaries much more effortless and save you extra time to spend on the things that are really important to you.