Towards Knowledge-Based Personalized Product Description Generation in E-commerce
Table 4. Attribute capturing score with different methods of Attribute Fusion.
['Model', 'Aspect (%)', 'User Category (%)']
Does our model capture characteristics of different attributes? The low accuracy for the baseline indicates that it is highly possible that the description of the baseline does not match the interested user group. On the contrary, KOBE generates descriptions that better reflect the intended attributes. KOBE obtains a 13.4% absolute gain in the accuracy for the attribute “user category”, and a 12.4% gain in the accuracy for the attribute “aspect”. This means that our model targets the intended user groups more accurately and it is more focused on a specific aspect.