Semalt Tells About The Most Powerful R Package In Website Scraping

RCrawler is powerful software that runs both web scraping and crawling at the same time. RCrawler is an R package that comprises inbuilt features such as detecting duplicated content and data extraction. This web scraping tool also offers other services such as data filtering and web mining.

Well-structured and documented data is hard to find. Large amounts of data available on the Internet and websites are mostly presented in unreadable formats. This is where RCrawler software comes in. RCrawler package is designed to deliver sustainable results in an R environment. The software runs both web mining and crawling at the same time.

Why web scraping?

For starters, web mining is a process that aims to collect information from data available on the Internet. Web mining is grouped into three categories that include:

Web content mining

Web content mining involves extraction of useful knowledge from site scrape.

Web structure mining

In web structure mining, patterns between pages becomes extracted and presented as a detailed graph where nodes stand for pages and edges stands for links.

Web usage mining

Web usage mining focuses on understanding the end-user behavior during site scrape visits.

What are web crawlers?

Also known as spiders, web crawlers are automated programs that extract data from web pages by following specific hyperlinks. In web mining, web crawlers get defined by the tasks they execute. For instance, preferential crawlers' focuses on a particular topic from the word go. In indexing, web crawlers play a crucial role by helping search engines crawl web pages.

In most cases, web crawlers' focuses on collecting information from website pages. However, a web crawler that extracts data from site scrape during crawling is referred to as a web scraper. Being a multi-threaded crawler, RCrawler scrapes content such as metadata and titles form web pages.

Why RCrawler package?

In web mining, discovering and gathering useful knowledge is all that matters. RCrawler is software that helps webmasters in web mining and data processing. RCrawler software comprises of R packages such as:

  • ScrapeR
  • Rvest
  • tm.plugin.webmining

R packages parse data from specific URLs. To collect data using these packages, you'll have to provide particular URLs manually. In most cases, end-users depend on external scraping tools to analyze data. For this reason, R package is recommended to be used in an R environment. However, if your scraping campaign dwells on specific URLs, consider giving RCrawler a shot.

Rvest and ScrapeR packages require the provision of site scrape URLs in advance. Luckily, tm.plugin.webmining package can quickly acquire a list of URLs in JSON and XML formats. RCrawler is widely used by researchers to discover science-oriented knowledge. However, the software is only recommended to researchers working in an R environment.

Some goals and requirements drive the success of RCrawler. The necessary elements governing how RCrawler works include:

  • Flexibility – RCrawler comprises of setting options such as crawling depth and directories.
  • Parallelism – RCrawler is a package that takes parallelization into account to better the performance.
  • Efficiency – The package works on detecting duplicated content and avoids crawling traps.
  • R-native – RCrawler effectively supports web scraping and crawling in the R environment.
  • Politeness – RCrawler is an R-environment based package that obeys commands when parsing web pages.

RCrawler is undoubtedly one of the most robust scraping software that offers basic functionalities such as multi-threading, HTML parsing, and link filtering. RCrawler easily detects content duplication, a challenge facing site scrape and dynamic sites. If you are working on data management structures, RCrawler is worth considering.