Sentiment learning on product reviews via sentiment ontology tree
Citation: Wei Wei and Jon Atle Gulla (2010) Sentiment learning on product reviews via sentiment ontology tree. Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (RSS)
Internet Archive Scholar (search for fulltext): Sentiment learning on product reviews via sentiment ontology tree
Download: http://dl.acm.org/citation.cfm?id1858681.1858723
Tagged: Computer Science
(RSS) ontologies (RSS), product reviews (RSS), sentiment analysis (RSS)
Summary
This paper points out that product reviews contain domain-specific knowledge. To capture the hierarchical relationships between product attributes, they introduce a new approach: "hierarchical learning with sentiment ontology tree" (HL-SOT) in order to:
- identify attributes
- identify which attributes have sentiment attached to them
This would enable searching for particular attributes in reviews.
Here is a sample sentiment ontology tree:
Their algorithm is based on H-RLS from Incremental algorithms for hierarchical classification. Evaluations are conducted against a human-labeled data set.
Selected references
- Nicolo` Cesa-Bianchi, Claudio Gentile, and Luca Zani-boni. 2006. Incremental algorithms for hierarchical classification. Journal of Machine Learning Re-search (JMLR), 7:31-54.
