Читать книгу Advanced Analytics and Deep Learning Models - Группа авторов - Страница 69

Inside this research activity, they tried to implement the new methods which manage criteria likings as contextual situations. To be specific, they trust that one portion of multi-criteria preferences may be observed as contexts and the other part managed in the conventional way in MCRS. They differentiate the suggestion efficiency between three settings. First one is applying every criteria rating in the conventional way. Second setting that they used is managing every criteria preference as contexts and the last one issuing preferred criteria ratings as contexts. Their demonstrations are depending on two practical rating datasets. It reveals that managing criteria priorities as contexts can upgrade the efficiency of module recommendations if those are being selected very carefully. They have used a hybrid model which selects criteria preference as contexts and solve remaining part in traditional way. They have illustrated this proposed model and got very efficient result and the model becomes the winner of their experiment [19].

Now, we will see its experimental evaluation and result to ensure its efficiency.