Dynamic Product Data Ingestion and Standardization
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Solution Overview
Problem
Users face difficulties in comparing and tracking online products across multiple webpages due to the need for manual data collection and lack of standardized formats, leading to information overload and inefficiencies in monitoring price changes and availability.
Innovation Solution
A system utilizing a trained machine learning algorithm to ingest and standardize product images and metadata from various webpages, allowing for dynamic monitoring and updates, even without predetermined templates, by analyzing search engine optimization metadata and prompting user input for missing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual data collection from multiple webpages is used, then data can be gathered from various sources, but user effort and time consumption increase significantly
Solution Approach 1:
The system performs automatic web scraping and data extraction without requiring user intervention. The automated system navigates multiple webpages, extracts product data, and compiles it into a standardized format, allowing the system to serve itself rather than requiring manual user operation for each data collection task
Solution Approach 2:
The system is designed to handle multiple types of product webpages from various sources through a unified interface. It can adapt to different webpage structures and extract relevant data automatically, making it versatile across multiple data sources while maintaining consistent output format
2Quantity of substance
If data from multiple webpages is collected manually, then comprehensive product information can be obtained, but data standardization becomes difficult
Solution Approach 1:
The system transforms data from various webpage formats into a standardized parameter structure. It identifies and extracts key parameters (product name, price, specifications, etc.) from different source formats and converts them into a unified data model, changing the parameter representation across all sources to a consistent standard
Solution Approach 2:
The system introduces an intermediary data processing layer between diverse webpage sources and the final standardized output. This intermediary layer handles format conversion, data validation, and standardization, acting as a mediator that reconciles different source formats into a unified structure without requiring changes to the original sources
3Speed
If real-time monitoring of product changes is implemented, then users receive immediate updates on price and availability, but system complexity increases
Solution Approach 1:
The system implements periodic monitoring of product webpages at scheduled intervals. Instead of continuous monitoring that would require constant system resources, it performs data extraction and change detection at regular periods, reducing system complexity while still providing timely update notifications to users
Solution Approach 2:
The system employs feedback mechanisms where extracted data is compared against previously stored data to detect changes. This feedback loop automatically identifies price changes, availability updates, or other modifications and triggers notifications only when actual changes are detected, reducing unnecessary processing while maintaining real-time awareness
4Productivity
If automated web scraping is used, then data collection efficiency improves, but handling webpages without predetermined templates becomes challenging
Solution Approach 1:
The system uses dynamic data extraction methods that adapt to different webpage structures. Instead of relying on fixed templates, it employs flexible parsing techniques that can adjust to various HTML structures and data formats encountered during web scraping, allowing high productivity while maintaining adaptability to unknown formats
Solution Approach 2:
The system performs preliminary analysis of webpage structures during the data collection process. It identifies data patterns and structures in advance before full extraction begins, allowing it to adapt its extraction strategy to each specific webpage format while maintaining efficient automated operation
Data Source
AI summary
A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform the steps of a method to dynamically ingest and monitor online products. The method may include receiving access to a webpage, determining whether the webpage includes a predetermined template, and in response to receiving the predetermined template, ingesting one or more product images and product metadata from the webpage. If no template is found, the system may request search engine optimization metadata to determine if at least one image is of a product before initializing a machine learning algorithm to determine whether the images correspond to product images. If no associated metadata is found, the system may request manual input of associated metadata before displaying, in real-time and in a standardized format, the ingested photos and metadata, allowing a user to select photos representing products of interest.