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Semalt Presents The Best Techniques And Approaches To Extract Content From Web Pages

Nowadays, the web has become the most extended data source in the marketing industry. E-commerce websites owners and online marketers rely on structured data to make reliable and sustainable business decisions. This is where web page content extraction comes in. To obtain data from the web, you require comprehensive approaches and techniques that will easily interact with your data source.

Currently, most web scraping techniques comprise of pre-packed features that allow web scrapers to use clustering and classification approaches to scrape web pages. For instance, to obtain useful data from HTML web pages, you'll have to pre-process the extracted data and convert the obtained data in the readable formats.

Problems that occur when extracting a core content from a web page

Most web scraping systems use wrappers to extract useful data from web pages. Wrappers work by wrapping information source using integrated systems and accessing the target source without changing the core mechanism. However, these tools are commonly used for a single source.

To scrape web pages using wrappers, you'll have to incur its maintenance costs, what makes the extraction process quite costly. Note that you can develop wrapper induction mechanism if your current web scraping project is on a large scale basis.

Web page content extraction approaches to consider

  • CoreEx

CoreEx is a heuristic technique that uses DOM tree to extract articles from online news platforms automatically. This approach works by analyzing the total number of links and texts in a set of nodes. With CoreEx, you can use Java HTML parser to obtain a Document Object Model (DOM) tree, which indicates the number of links and texts in a node.

  • V-Wrapper

V-Wrapper is a quality template-independent content extraction technique widely used by web scrappers to identify a primary article from the news article. V-Wrapper uses MSHTML library to parse HTML-source to obtain a visual tree. With this approach, you can easily access data from any Document Object Model nodes.

V-Wrapper uses parent-child relation between two-target blocks, which later defines the set of extended features between a child and a parent block. This approach is designed to study online users and identify their browsing behaviors by using manually selected web pages. With V-Wrapper, you can locate visual features such as banners and advertisements.

Nowadays, this approach is widely used by web scrapers to identify features in a web page by looking into the main block and determining the news body and the headline. V-Wrapper uses extraction algorithm to extract content from web pages which entail identifying and labeling the candidates block.

  • ECON

Yan Guo designed ECON approach with a primary aim of automatically retrieving content from web news pages. This method uses HTML parser to convert web pages into a DOM tree fully and utilizes the comprehensive features of the DOM tree to obtain useful data.

  • RTDM algorithm

Restricted Top-Down Mapping is a tree edit algorithm based on traversal of trees where the operations of this approach are restricted to the target-tree leaves. Note that RTDM is commonly used in data labeling, structure-based web page classification, and extractor generation.

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