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Imagine the worst literary product possible — in other words, the most inappropriate commercial item based on a famous book or author.
That item, based on a single unnamed source, was published on the front page of several newspapers, including Pakistan's largest, The Daily Jang.
But despite the fact it has been dealt with formally elsewhere, decency demands I make a WTF-strewn apology for last week's triumph, which saw an entire Steven Seagal item based on something fictional.
The food industry's classic response is to say that the ingredients are listed on the label, knowing full well that many consumers will purchase a food item based upon the way it's promoted, not its nutritional content.
However, this did not prevent these patients from completing the item based on their interpretation.
Fab's collaborative filtering technology uses Apache Mahout's machine learning libraries, which also includes support for user and item based recommendations.
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Hybrid user-item based collaborative filtering (HCF) [22] is the hybrid recommendation approach which integrates the user-based nearest neighbor recommendation with the item-based nearest neighbor recommendation.
The experimental results are shown in Figures 1 and 2. Figure 1 Comparison of PF algorithm and user-based CF, item-based CF with MAE. Figure 2 Comparison of PF algorithm and user-based CF, item-based CF with RMSE.
Memory-based CF can also be distinguished into: user-based and item-based.
Currently, Mahout offers implementations for user-based recommendations, item-based based recommendations, and several variations of matrix factorization.
Compared with the used-based CF and item-based CF, the proposed method PF has higher predictive accuracy.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com