Web Data Mining is the process of extracting useful information from websites using various techniques such as web scraping, web data extraction, data harvesting, web crawling, and data mining. Simply put, it is a practice that allows businesses to capture valuable insights from online sources.
If you're looking for a more creative definition, think of it this way - Web Data Mining is like digging for gold in an endless field of digital dirt. You use specific tools to sift through layers upon layers of information until you find the nuggets that are relevant and valuable.
Web scraping refers to the technique used by software programs to extract relevant information from websites. This technique uses automated tools or bots to crawl through multiple pages on a website while capturing pieces of structured data.
Think about it as if you're collecting puzzle pieces scattered across several different places on a webpage; only here we're looking for specific types of puzzles we want our algorithm or code snippet to solve.
Web Data Extraction involves gathering unstructured or semi-structured content (like forum posts or product reviews) from different sites. Once extracted with powerful algorithms/tools/constants yields patterned/format content which can be processed easier/given sense with machine learning-based NLP models.
Plainly speaking: When you go fishing at sea where there's an abundance but random selection/competition influences your take-home result/quality; we'll wait at mouth-watering points where concrete patterns/impressions were observed--- Like shoals gathering around harbor, chart their activity 'n show upcoming tide report over seascape!
Data harvesting refers to collecting large amounts of raw digital data using certain automated software technologies. The aim here usually being quantitative rather than qualitative so the subsequent reasoning may consist AI-driven predictions instead comparisons given by manual oversight methods otherwise known as brushing/mopping floors area after area.
If you think about it as a farmer, they plan to grow crops across the year in different seasons and maximize their yield using machines that harvest based on pre-made decisions.
Web crawling is essentially automating the process of discovering new content/links within websites by following links from one page to another. This can be concluded with various forms such as https://www.google.com/search?q=covid+19 . This helps businesses keep up-to-date with changes and monitor competitors better.
Think Gizmo's questing for extra goodies encountered during his toy shop heist!
Data mining simply means identifying patterns or relationships between large datasets often considered too big/small for human interpretation (Machine Learning). By analyzing website usage data, marketers gain valuable insights into browsing history/channels/frequency sentiments towards certain interactions giving them smoother roadways towards product discovery/in-content advertising engagement opportunities which otherwise would be hidden in the massive quantity of data itself.
It's like having your own personal Harry Potter invisibility cloak. You wear it while walking through a store where all conversations disappear except for specific customers discussing information relevant to you personally.
1) Pang-Ning Tan et al., Introduction To Data Mining (3rd Edition)
2) Anon., Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models(3rd edition).
3) Muhammad Sarwar et al., Text Mining: Classification, Clustering, and Applications(12th Edition).
4) Hadley Wickham R & Garrett Grolemund, R For Data Science (1st edition), O'Reilly Media Inc..
5) Mathew Scarpino , XPath Essentials - XML Path Language For Employable Work Force (6th edition).
