sidoki
sidoki
Hi @spro, If i can conclude, instead of using location-based this tutorial using content-based, right? so there is no need to define the max_length anymore. How about the evaluation process?...
Got it @spro By the way, i have additional question regarding to training process. If i skim your code, the selection of sample training data was done by random choice...
Thanks @spro, I see, glad to hear that there will be implementation for batch process. Can't wait for that!
Hi @BitcoinKing , I Think you can just use your own datasets in Russian language that follow format exactly like training data in this repo
Hi @ganeshjawahar, can you elaborate more about bug in data.py ? What should i change? Thank you!
Hi @0220joey, So, the aspect term should be annotate first as input alongside with the review text? Or the model can extract it automatically? Thank you
Hi @0220joey, i see, so everytime we would like to predict unseen review data, we should know the list of aspect term first, right? I thought the model can automatically...
Because it is aspect-based sentiment analysis. So, instead of predicting overall sentiment for given text input. The model should be able to extract valid aspects and define its polarity. Back...
Hi @0220joey, Thanks for detail explanation. So, if i can infer from your statement, the model explained on the paper cannot automatically extract predefined category of aspect (e.g.: food, service)...
Can you share where is the location of original author code? Thank you