Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/www2008/paper/153> ?p ?o. }
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- 153 creator ivan-titov.
- 153 creator ryan-mcdonald.
- 153 type InProceedings.
- 153 label "Modeling Online Reviews with Multi-grain Topic Models".
- 153 sameAs 153.
- 153 abstract "In this paper we present a novel framework for extracting the ratable aspects of objects from online user reviews. Extracting such aspects is an important challenge in automatically mining product opinions from the web and in generating opinion-based summaries of user reviews. Our models are based on extensions to standard topic modeling methods such as LDA and PLSA to induce multi-grain topics. We argue that multi-grain models are more appropriate for our task since standard models tend to produce topics that correspond to global properties of objects (e.g., the brand of a product type) rather than the aspects of an object that tend to be rated by a user. The models we present not only extract ratable aspects, but also cluster them into coherent topics, e.g., ``waitress'' and ``bartender'' are part of the same topic ``staff'' for restaurants. This differentiates it from much of the previous work which extracts aspects through term frequency analysis with minimal clustering. We evaluate the multi-grain models both qualitatively and quantitatively to show that they improve significantly upon standard topic models.".
- 153 hasAuthorList authorList.
- 153 hasTopic World_Wide_Web.
- 153 isPartOf proceedings.
- 153 keyword "clustering".
- 153 keyword "opinion mining".
- 153 keyword "topic models".
- 153 title "Modeling Online Reviews with Multi-grain Topic Models".