Transfer Learning For Prediction Of Sentiment In Hotel Reviews
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Abstract
The web platforms have made people share thoughts, write reviews and make a huge source of information. These web platforms can be online news, blogs, community’s discussion forum. People visited any hotel write their reviews on these forums. Understand manually all the text written becomes complex because people express their views in the different and complex ways. For instance, the online reviews given on hotel services and quality, it is difficult to understand the reviews manually. To make certain decision on improving the quality and service of the hotel it will be inconvenient to read the reviews manually. In this concern, the paper aims to develop a deep learning technique and transfer learning with word embeddings to analyse hotel review for identifying the response strategies. We have also proposed a new combined model, which integrates machine learning and convolutional neural network models with GloVe Embeddings to analyse the text. The obtained results show that proposed new model can outperform compare to other machine learning techniques.
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