In this work, we propose using four sources of information: product description, product specification, customer reviews, and question-answers for aspect-sentiment-based opinion summarization. We use a transfer-learning approach to fine-tune a pre-trained model to generate summaries.
Jan 4, 2023 · In this work, we propose using four sources of information: product description, product specification, customer reviews, and question-answers ...
This work proposes using four sources of information: product description, product specification, customer reviews, and question-answers for ...
Opinion summarization focuses on generating summaries that reflect popular opinions of multiple reviews for a single entity (e.g., a hotel or a product.) While ...
In this work, we propose using four sources of information: product description, product specification, customer reviews, and question-answers for aspect- ...
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What is opinion summarization in sentiment analysis?
What is text summarization using sentiment analysis?
“Low-level annotations and summary representations of opinions for multi-perspective question answering.” New Directions in Question Answering (2004). Google ...
The first phase is the aspect-based representation used to represent ranked knowledge on aspect opinion calculated by using frequencies, polarity, and opinion ...
Definition 2.10 in Chapter 2 defined a structured opinion summary called aspect-based summary, also known as feature-based summary in the reports by Hu and Liu ...
Sep 17, 2024 · Aspect-based sentiment analysis (ABSA) is a fine-grained type of sentiment analysis that identifies aspects and their associated opinions ...
Oct 22, 2024 · This study augments the pointer generator framework with opinion feature extraction, feature pooling, and mutual attention mechanism for opinion ...