_analyzing-sentiments-in-one-go-a-supervised-joint-topic-modeling-approach-124-final-year-project-2018.jpg "Analyzing Sentiments in One Go: A Supervised Joint Topic Modeling Approach | Final Year Project 2018. from live video call chat online Video Screenshot Preview")
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⏲ Duration: 7 min 83 sec
✓ Published: 09-Apr-2018
✓ Published: 09-Apr-2018
Description:
SJASM represents each review document in the form of opinion pairs, and can simultaneously model aspect terms and corresponding opinion words of the review for hidden aspect and sentiment detection. It also leverages sentimental overall ratings, which often comes with online reviews, as supervision data, and can infer the semantic aspects and aspect-level sentiments that are not only meaningful but also predictive of overall sentiments of reviews.nnIncluding Packages n======================= n*
SJASM represents each review document in the form of opinion pairs, and can simultaneously model aspect terms and corresponding opinion words of the review for hidden aspect and sentiment detection. It also leverages sentimental overall ratings, which often comes with online reviews, as supervision data, and can infer the semantic aspects and aspect-level sentiments that are not only meaningful but also predictive of overall sentiments of reviews.nnIncluding Packages n======================= n*
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