Google Panda: Avoiding duplicated content

1) Single exports
2) Comparative exports
3) The little extras


1) Single exports

You have composed an article, organizing it into paragraphs and sections of options.
You have selected the three dictionaries.
You have continued to the choice of expressions and equivalents.
You would now like to generate different versions of your article.

You can select either a single text at random, or 10 texts, 20 texts or 50 texts.

Human Easy Spinner then proceeds to establish these texts.

To this end, it takes into account the structure of your articles, the dictionaries and their priorities, the expressions and their equivalents, starting with the longest expressions and the quality settings.

Human Easy Spinner thus offers you a range of different texts, the number of which may be lower than or equal to the number of texts requested.

Basically, if the quality settings are strict and the article has few combination options, the number of different texts is therefore reduced but will remain in the Google Panda clipboard.


2) Comparative exports

Comparative exports are based on the same principle as single exports. Google Panda may detect your previous articles as duplicate content with your new texts. It is therefore important to take this into account for your new texts.

On the other hand, you may select a folder containing documents in text format (.txt) encoded in UTF-8.

Human Easy Spinner takes these texts into consideration when generating the output texts so that the latter are not just different than each other but also different than the texts in the chosen folder.


3) The little extras

Control of the number of attempts to obtain the number of output texts closest to the volume requested.

Quality control to obtain output texts which are as different as possible.
The higher the quality, the more difficult it is to obtain the desired number of output texts. In fact, the higher the quality, the more different the texts must be to each other.

The algorithm developed is not content to replace the expressions with equivalents, it compares the texts with each other to ensure it only retains those texts which do not resemble others in terms of the above criteria.

Human Easy Spinner does not use the distance theory of Levenshtein, the distance theory developed by Hamming nor Jaccard’s algorithm, not very tried and tested methods for use in creating spin…

The method used by Google to detect duplicate content is not particularly well known but you can imagine that an algorithm based on impressions would be a good idea.