Sandro Cavallari, PhD Candidate, NTU
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Aspect Extraction
- based on frequent words (occurrences and co-ocurrences of noun and noun phrases)
- by exploiting opinion and target relations
- based on topic modelling
- based on supervised learning
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Deep convolutional belief network
- composition of the unsupervised RBM
- trained layer wise to maximise a energy function
Sentic-net: extract the linguistic pattern as additional information
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Dataset
- Word Embedding
- Random
- Google word2vec embedding
- Our amazon embedding(~34 reviews)
- Evaluation copra
- Aspect-based sentiment analysis [Qui et al.]
- SemEval 2014
- Postag
- Stanford tagger to detect 6 basic part of speech
- Word Embedding
