How Crowd Computing Solves Data Scraping

Data scraping solved the problem of making human-readable content readable by machines, but current scraping solutions have created new problems for enterprise users. The formats of data sources change with increasing frequency as data volumes soar, and the algorithms that power scrapers collect irrelevant information and require human intervention to adapt. This not only creates cost but also data downtime. Crowd computing solves this problem by pairing machine learning with human intelligence to train and improve scraping algorithms, ensuring efficient, relevant and unbreakable extraction.

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