Machine Learning Company Data Mining
We designed a machine learning-powered web scraper to extract key data from diverse company websites. Using natural language processing (NLP) techniques, the system quickly identifies and gathers high-value information from web pages.
BERT-based NLP model for understanding website content and structure
AI-powered web scraper for semantic content extraction
3x faster data collection than traditional web crawlers
Challenge
The manual collection of data from company websites was slow and inefficient, particularly when dealing with large-scale data extraction needs. Traditional web crawlers struggled to adapt to varying page structures.
Solution
We developed a machine learning-based web scraper using a BERT model to semantically understand webpage structures. The scraper identifies high-value data and extracts it quickly, even across varying site layouts.
Results
The system delivered a 3x increase in data collection speed, allowing for rapid aggregation of critical information from company websites and streamlining business processes.
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