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Natural language processing / Learning / Beer culture / Beer rating / Sentiment analysis / Grammatical aspect / Semi-supervised learning / Supervised learning / Support vector machine / Machine learning / Artificial intelligence / Statistics


Learning Attitudes and Attributes from Multi-Aspect Reviews Julian McAuley, Jure Leskovec, Dan Jurafsky Stanford University Abstract—Most online reviews consist of plain-text feedback together with a single numeric sco
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Document Date: 2012-11-09 01:36:44

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Company

Online LDA / Local LDA / Amazon / TigerDirect / Netflix / Yahoo! Hotels / oDesk / MultiGrain LDA / DP-Review / B. Review / Do / TripAdvisor / Boeing / Samsung / BizRate / Intel / Microsoft / /

Country

Jordan / /

Event

Product Recall / Man-Made Disaster / Product Issues / /

IndustryTerm

few hours using commodity hardware / segmentation algorithms / product rating systems / multiaspect review systems / recommender systems / similar rating systems / review systems / food / multi-aspect rating systems / na¨ıve solution / computer vision applications / /

Movie

We shall see / /

Organization

National Science Foundation / Stanford University / /

Person

Mary Bechmann Foun / PALE L AGER / Dan Jurafsky / Semi-Supervised Learning / Albert Yu / Paul Heymann / Alfred P. Sloan / /

Position

works model the relationship / first author / light tan head / minimal lace and low retention / segmentation and rating model / unsupervised aspect-sentiment model for online reviews / author / model / light tan head / text and rating model / representative / Aspect and sentiment unification model for online review analysis / /

Product

Pentax K-x Digital Camera / Maxent classifier / Figure / /

ProgrammingLanguage

C / /

Technology

Kuhn-Munkres algorithm / carbonation / semi-supervised algorithm / segmentation algorithms / unsupervised algorithm / Data Mining / /

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