A Recommendation System Using Aspect Analysis and Deep Learning

  • 陳 立欣

Student thesis: Doctoral Thesis


In recent years the recommendation system has been applied in all walks of life Most of the traditional recommendation system practices rely on the user’s historical information or item characteristics to recommend a suitable choice But the recommendation system combined with sentiment analysis usually uses the overall product evaluation as the feature basis it is hard to understand the preference of individual products from the detailed information We propose the concept of latent aspect input the comment sentence into the deep learning model and extract the feature vector from the sentence We Use the Attention mechanism to assign each part of the input to different importance levels assign higher weights to the Aspect comment description of users’ attention Our goal is to extract key Aspect comment features combining with a probability matrix decomposition method for interactive training applied to the recommendation system to achieve better recommendation results
Date of Award2019
Original languageEnglish
SupervisorRen-Shiou Liu (Supervisor)

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