AliHaiderAhmad001/Stacked-Embeddings-and-Ensemble-Model-based-Sequence-Labeling-for-Aspect-Extraction
Graduation project for a bachelor's degree in informatics engineering (Artificial Intelligence specialization).
This project helps businesses understand customer feedback by automatically identifying specific product features or attributes mentioned in reviews. You provide raw text from customer opinions, and it highlights the exact aspects being discussed, like 'battery life' or 'speed'. This tool is for market researchers, product managers, or customer service analysts who need to quickly pinpoint what customers are talking about in their reviews.
No commits in the last 6 months.
Use this if you need to systematically extract product features or aspects from a large volume of customer reviews to understand sentiment at a granular level.
Not ideal if you only need general sentiment (positive/negative) without drilling down into specific product attributes.
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Python
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Last pushed
Apr 20, 2023
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