all AI news
Enhanced Review Detection and Recognition: A Platform-Agnostic Approach with Application to Online Commerce
May 14, 2024, 4:49 a.m. | Priyabrata Karmakar, John Hawkins
cs.CL updates on arXiv.org arxiv.org
Abstract: Online commerce relies heavily on user generated reviews to provide unbiased information about products that they have not physically seen. The importance of reviews has attracted multiple exploitative online behaviours and requires methods for monitoring and detecting reviews. We present a machine learning methodology for review detection and extraction, and demonstrate that it generalises for use across websites that were not contained in the training data. This method promises to drive applications for automatic detection …
abstract application arxiv commerce cs.ai cs.cl detection generated importance information machine monitoring multiple platform products recognition review reviews type unbiased
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)
@ HelloBetter | Remote
Doctoral Researcher (m/f/div) in Automated Processing of Bioimages
@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena
Seeking Developers and Engineers for AI T-Shirt Generator Project
@ Chevon Hicks | Remote
Principal Data Architect - Azure & Big Data
@ MGM Resorts International | Home Office - US, NV
GN SONG MT Market Research Data Analyst 11
@ Accenture | Bengaluru, BDC7A