Papers with KPs

3 papers
Aspect-based Key Point Analysis for Quantitative Summarization of Reviews (2024.findings-eacl)

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Challenge: Existing studies on review summarization use only major opinions, but ignore minority opinions and fail to quantify opinion prevalence.
Approach: They propose a framework for quantitative review summarization using aspect-based key point analysis (ABKPA) they use aspect-basic sentiment analysis to automatically annotate silver labels for matching aspect-sentiment pairs .
Outcome: The proposed framework outperforms state-of-the-art baselines on Yelp reviews on five business categories.
Towards the Inference of Semantic Relations in Complex Nominals: a Pilot Study (L18-1)

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Challenge: Complex nominals (CNs) show similar external forms but encode different semantic relations because of noun packing.
Approach: They propose to use paraphrases to convey conceptual content of english two-term CNs in the domain of environmental science to disambiguate the semantic relation between constituents of CN.
Outcome: The proposed method disambiguates the semantic relation between constituents of the CN and infers the semantic relations in these multi-word terms.
Prompted Aspect Key Point Analysis for Quantitative Review Summarization (2024.acl-long)

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Challenge: Recent abstractive approaches generate KPs based on sentences, resulting in overlapping and hallucinated opinions.
Approach: They propose to use supervised learning to extract short sentences as key points before matching them to review comments for quantification of KP prevalence.
Outcome: The proposed framework achieves state-of-the-art performance on Yelp and SPACE.

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