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Effective Anomaly Detection Pipeline for Amazon Reviews: References & Appendix

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Manage episode 426250797 series 3474148
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/effective-anomaly-detection-pipeline-for-amazon-reviews-references-and-appendix.
Explore findings from a study on an anomaly detection pipeline for Amazon reviews using MPNet embeddings.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #transformers, #anomaly-detection, #nlp-for-anomaly-detection, #explainability-in-ml, #machine-learning-classifiers, #text-specific-ad-models, #text-encoding-techniques, #explainable-ai, and more.
This story was written by: @textmodels. Learn more about this writer by checking @textmodels's about page, and for more stories, please visit hackernoon.com.
This study introduces an effective pipeline for detecting anomalous Amazon reviews using MPNet embeddings. It evaluates SHAP, term frequency, and GPT-3 for explainability, revealing user preferences and computational challenges. Future research may explore broader surveys and integrating GPT-3 throughout the pipeline for enhanced performance.

  continue reading

316 episodes

Artwork
iconShare
 
Manage episode 426250797 series 3474148
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/effective-anomaly-detection-pipeline-for-amazon-reviews-references-and-appendix.
Explore findings from a study on an anomaly detection pipeline for Amazon reviews using MPNet embeddings.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #transformers, #anomaly-detection, #nlp-for-anomaly-detection, #explainability-in-ml, #machine-learning-classifiers, #text-specific-ad-models, #text-encoding-techniques, #explainable-ai, and more.
This story was written by: @textmodels. Learn more about this writer by checking @textmodels's about page, and for more stories, please visit hackernoon.com.
This study introduces an effective pipeline for detecting anomalous Amazon reviews using MPNet embeddings. It evaluates SHAP, term frequency, and GPT-3 for explainability, revealing user preferences and computational challenges. Future research may explore broader surveys and integrating GPT-3 throughout the pipeline for enhanced performance.

  continue reading

316 episodes

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