ZZZ_Related Work - GetRecced/IR670_Spring2018 GitHub Wiki

Some of the researchers have tried getting topics explicitly from user in addition to the overall ratings.

1. S.Baccianella, A.Esuli, and F.Sebastiani. Multi-facet rating of product reviews. In ECIR, 2009.
2. Y.Jo and A.Oh. Aspect and sentiment unification model for online review analysis. In WSDM, 2011.
3. B.Lu, M.Ott, C.Cardie, and B.Tsou. Multi-aspect sentiment analysis with topic models. In Workshop on SENTIRE, 2011.
4. I.Titov and R.McDonald. A joint model of text and aspect ratings for sentiment summarization. In ACL, 2008.

Extracting topics automatically based on frequently occuring noun phrases or grammatical rules is also tried.

1. M.Hu and B.Liu. Mining and summarizing customer reviews. In KDD, 2004.
2. A.Popescu and O.Etzioni. Extracting product features and opinions from reviews. In HLT, 2005.

Combining review text with product features was the main goal of a paper on LDA.

1. D.Blei, A.Ng, and M.Jordan. Latent dirichlet allocation. JMLR, 2003.