The main content in a webpage is usually centered and visible without the need to scroll. It is often rounded by the navigation menus of the website and it can include advertisements, panels, banners, and other not necessarily related information. The process to automatically extract the main content of a webpage is called content extraction. Content extraction is an area of research of widely interest due to its many applications. Concretely, it is useful not only for the final human user, but it is also frequently used as a preprocessing stage of different systems (i.e., robots, indexers, crawlers, etc.) that need to extract the main content of a web document to avoid the treatment and processing of other useless information. In this work we present a new technique for content extraction that is based on the information contained in the DOM tree. The technique analyzes the hierarchical relations of the elements in the webpage and the distribution of textual information in order to identify the main block of content. Thanks to the hierarchy imposed by the DOM tree the technique achieves a considerable recall and precision. Using the DOM structure for content extraction gives us the benefits of other approaches based on the syntax of the webpage (such as characters, words and tags), but it also gives us a very precise information regarding the related components in a block (not necessarily textual such as images or videos), thus, producing very cohesive blocks.
Use of Word to leaf ratio (WLR) REF for content extraction is a new approach.
Using the words/leafs ratio in the DOM tree for content extraction
J. Log. Algebr. Program.
J. Log. Algebr. Program.
Computer Science Mathematics