Extending ChatGPT with a Browserless System for Web Product Price Extraction

TL;DR

This paper introduces Wextractor, a system that extends ChatGPT to perform web-based product price extraction, enabling it to answer specific transactional questions by integrating web data retrieval techniques.

Contribution

The paper presents Wextractor, a novel system that enhances ChatGPT's capabilities with web data extraction features for transactional queries, including social and pointing pattern extraction improvements.

Findings

Wextractor successfully retrieves product prices from the web.

The system improves answer speed through pattern extraction techniques.

It extends ChatGPT's functionality for specific web-based queries.

Abstract

With the advenement of ChatGPT, we can find very clean, precise answers to a varied amount of questions. However, for questions such as 'find the price of the lemon cake at zingerman's', the answer looks like 'I can't browse the web right now'. In this paper, we propose a system, called Wextractor, which extends ChatGPT to answer questions as the one mentioned before. Obviously, our system cannot be labeled as `artificial intelligence'. Simply, it offers to cover a kind of transactional search that is not included in the current version of ChatGPT. Moreover, Wextractor includes two improvements with respect to the initial version: social extraction and pointing pattern extraction to improve the answer speed.