Knowledge Transfer and Opinion Detection in the TREC2006 Blog Track
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TL;DR
The paper describes the opinion detection system developed in Carnegie Mellon University for TREC 2006 Blog track, which performed a two-stage process: passage retrieval and opinion detection.
Abstract
The paper describes the opinion detection system developed in Carnegie Mellon University for TREC 2006 Blog track. The system performed a two-stage process: passage retrieval and opinion detection. Due to lack of training data for the TREC Blog corpus, online opinion reviews provided in other domains, such as movie review and product review, were used as the training data. Knowledge transfer was performed to make the cross-domain learning possible. Logistic regression ranked the sentence-level opinions vs. objective statements. The evaluation shows that the algorithm is effective in the task.