Discourse Level Explanatory Relation Extraction from Product Reviews Using First-Order Logic
Sentiment Analysis
Relationship extraction
DOI:
10.18653/v1/d13-1097
Publication Date:
2024-11-27T23:52:27Z
AUTHORS (5)
ABSTRACT
Explanatory sentences are employed to clarify reasons, details, facts, and so on. High quality online product reviews usually include not only positive or negative opinions, but also a variety of explanations why these opinions were given. These can help readers get easily comprehensible information the discussed products aspects. Moreover, explanatory relations benefit sentiment analysis applications. In this work, we focus on task identifying subjective text segments extracting their corresponding from in discourse level. We propose novel joint extraction method using firstorder logic model rich linguistic features long distance constraints. Experimental results demonstrate effectiveness proposed method.
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