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Matching Product Information from the Web for Comparisons

Technology Overview

The technology is a know-how to improve the process of obtaining data about product entities from the Web. As information about a particular product is found in separate e-commerce platforms, this know-how involves a suite of algorithms to crawl data in a robust manner, as well as to match entity information obtained from disparate e-commerce websites. The matched product information allows applications such as price and product intelligence, pricing automation, competition analysis. The target users for this technology are businesses seeking data for competitive analysis as well as end-consumers seeking efficient price comparison prior to purchase. We are seeking partners to collaborate to develelop the solution towards effective proof-of-concepts for commercialization.

Technology Features, Specifications and Advantages

The technology features three main capabilities.

First, it increases data retrieval capacity and frequency of information retrieval from online e-commerce sites through intelligent scheduling, resource allocation, and randomization of requests. This confers the advantage of increased recency and freshness of data of competitors to better stay up to date.

Second, it improves the matching of identical products from different e-commerce sites with the use of machine learning technologies. The algorithm continually improves over time with experience and feedback on matching quality. This allows more accurate matching of products, providing higher quality price intelligence.

Third, it supports all-in product comparisons, including products to be purchased from abroad, after accounting for shipping, taxes, etc. This allows consumers a convenient and transparent means for comparing product offers.

Potential Applications

The primary application area is pricing intelligence via monitoring how the same product is featured across e-commerce sites.

Specific applications may include :

  • recommending product pricing based on competition's pricing
  • finding arbitrage opportunities from different pricing levels of the same product across regions
  • assessing and monitoring market competitiveness
  • enabling convenient price comparison features

Customer Benefit

Customers can look forward to various benefits.

  • Saving time and cost of labour, as surfing through multiple e-commerce sites to obtain competitive pricing information is tedious and requires manpower
  • Obtaining more representative comparisons, as matching products across sites is often difficult as the same product may be described differently
  • Saving purchasing cost as finding better offers would lower operational cost and potentially increase profit of company
  • Obtaining environmental benefits via improving logistical flow by reducing the need to store stocks in intermediaries, which could potentially improve carbon footprint
Contact Person

Francis Lim


Singapore Management University - School of Computing and Information Systems

Technology Category

  • Infocomm
  • Artificial Intelligence, Enterprise & Productivity, Natural Language Processing & Semantic Technology, Video/Image Analysis

Technology Readiness Level


e-commerce, web, scraping, crawling, matching, algorithm, products, comparison, automation, text, image, nlp, productivity