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Document Annotation Using Mapping Attribute Value
Abstract
Today’s data is rapidly and continuously growing and is not constant in nature. To deal with such kind of extracting data, as it is to annotate data, mapping attribute value is a solution. In Number of organization or company generate and share their textual information of their products, facilities, and services. Such collections of textual data contain a significant amount of structured data, which is hidden in the unstructured text document. Whereas information extraction systems simplify the extraction of structured associations, they are frequently expensive and incorrect, particularly when working on top of text that does not comprise any examples of the targeted structured data. Projected an alternative methodology that simplifies the structured metadata generation by recognizing documents that are possible to contain information of awareness and this data will be beneficial for querying the database. Additionally, we propose an algorithm that mapping attribute-value pair to manually generated schemas for product data.
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