Existing works on sentiment analysis on product reviews suffer from the following limitations: (1) The knowledge of hierar- chical relationships of products attributes is not fully utilized. (2) Reviews or sen- tences mentioning several attributes asso- ciated with complicated sentiments are not dealt with very well. In this paper, we pro- pose a novel HL-SOT approach to label- ing a product’s attributes and their asso- ciated sentiments in product reviews by a Hierarchical Learning (HL) process with a defined Sentiment Ontology Tree (SOT). The empirical analysis against a human- labeled data set demonstrates promising and reasonable performance of the pro- posed HL-SOT approach. While this pa- per is mainly on sentiment analysis on re- views of one product, our proposed HL- SOT approach...

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