Web scraping is a technique that extracts information or automatically collecting information from the web. Web scraping can be used to convert unstructured data on the web, usually in HTML format, into structured data. This makes it easier to store it in a centralized database or spreadsheet.
Data mining, on the other hand, involves determining patters in large data sets using a mix of techniques like artificial intelligence, machine learning, statistics, and database systems. The primary aim of data mining is to extract information from any data set and convert it into structured data for better understanding. It is a closely-related process to Web scraping, only a lot more advanced. Data mining involves not only a raw, initial analysis of data but also includes the concepts of database management, data pre-processing, post-processing of discovered structures, model and interface considerations, complexity considerations and a lot more disciplines. The tasks involved in data mining are anomaly detection, association rule learning, clustering, classification, regression, and summarization.
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