Packaging in data mining is a program that extracts the content of a particular information source and translates it into a relational form. Many web pages present structured data - phone directories, product catalogs, etc. that are formatted for human searches using HTML. Structured data is usually a description of the object retrieved from the underlying database and displayed in a webpage following some fixed templates. Software systems that use such resources must translate HTML content into relational form. Packaging is usually used as a translator of the kind. Formally, wrapping is a function of the page to the set of tuples it contains.
Video Wrapper (data mining)
Packaging generation
There are two main approaches for wrapping wrap: packing induction and automatic data extraction. The wrapper induction uses supervised learning to study data extraction rules from manually labeled training samples. Disadvantage induction wrapper is
- time-consuming and manual labeling process
- trouble with wrapping treatments.
Due to manual labeling efforts, it is difficult to extract data from a large number of sites because each site has its own template and requires separate manual labeling for learning wrappers. Wrapper treatment is also a big issue because every time a site changes the wrappers that are built for the site it becomes obsolete. Due to these deficiencies, researchers have studied the generation of automatic wrapping using unattended pattern mining. Automatic extraction is possible because most Web data objects follow a fixed template. Finding such a template or pattern allows the system to execute automatically. Recently, increased availability of Linked Data has enabled methods that can automatically learn and maintain wrappers using these resources, based on the principle of 'remote control'. In this case, the example example concept was first collected from the Related Data Sets available to the public. These are then searched in a collection of Web pages and events that match them annotated. While these annotations can be noisy, they are proven to be useful training data to learn about wrapping webpages.
Web generation wrappers are an important issue with many applications. The data extraction allows one to integrate data/information from multiple websites to provide value-added services, for example, comparative shopping, object search, and information integration. - The wrapping content can be improved
Maps Wrapper (data mining)
See also
- Business intelligence (Semi-structured or unstructured Data section)
- Web scraping
Source
Source of the article : Wikipedia
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