id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_k5zsbz3e7jfnxis6togjuxtjze	Aiqi Jiang	Leveraging aspect phrase embeddings for cross-domain review rating prediction	2019	21	.pdf	application/pdf	9428	969	63	Keywords Aspect phrase embeddings, Review rating prediction, Sentiment analysis, Social media, Cross-domain reviews, Yelp, Amazon, TripAdvisor, Word embeddings, Multinomial logistic Leveraging aspect phrase embeddings for cross-domain review rating prediction. different aspects that vary across domains, can be effectively leveraged for the review rating To the best of our knowledge, review rating prediction for non-popular domains has To enable our analysis of review rating prediction over different domains, we make use of review rating prediction, where the training and test data belong to the same domain. we show and analyse the results for cross-domain review rating prediction, where data from Tables 3 and 4 show results for in-domain review rating prediction, where the training Table 7 MAE Results for cross-domain review rating prediction with different percentages of the Table 8 RMSE Results for cross-domain review rating prediction with different percentages of the to propose a cross-domain review rating prediction system that would perform well for	./cache/work_k5zsbz3e7jfnxis6togjuxtjze.pdf	./txt/work_k5zsbz3e7jfnxis6togjuxtjze.txt