Summary of Enhanced Review Detection and Recognition: a Platform-agnostic Approach with Application to Online Commerce, by Priyabrata Karmakar et al.
Enhanced Review Detection and Recognition: A Platform-Agnostic Approach with Application to Online Commerce
by Priyabrata Karmakar, John Hawkins
First submitted to arxiv on: 9 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel machine learning-based methodology for detecting and extracting online reviews is presented, which demonstrates generalizability across websites not included in the training data. The approach has potential applications for automatic review detection and evaluation, regardless of source. Key features include Sentiment Inconsistency Analysis, Multi-language support, and Fake review detection, achieved through integrating a trained NLP model to identify genuine versus fake reviews. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Online commerce relies on user-generated reviews to provide unbiased product information. However, this has led to exploitative behaviors and the need for methods to monitor and detect reviews. A machine learning-based approach is introduced that can detect and extract reviews across various websites, including those not in the training data. This method has many applications, such as identifying unreliable reviews by detecting inconsistencies between ratings and comments, supporting multiple languages without HTML scraping, and detecting fake reviews. |
Keywords
» Artificial intelligence » Machine learning » Nlp
