Data entry processing is widely known method for collecting and storing information. Manual data entry is utilized extensively in numerous industries to gather data and maintain databases. However, manual data entry is often a tedious, time consuming and labor intensive task. Additionally data entry processing may be quite costly, often requiring companies to hire additional employees to accomplish data entry tasks, or outsource data entry tasks to data entry specialists. Further, because data entry is typically performed manually, the process is highly error-prone.
With the advent of e-commerce, consumers and businesses alike are often required to provide information to other parties via the Internet, usually by completing a web-based form or set of forms. Software tools have been developed to reduce data entry workload by automatically filling in empty data fields for certain types of forms. Such software programs have the ability to assist data entry by accessing predefined user information and filling in blank forms with the appropriate stored data. However, these programs are generally utilized by Hyper Text Markup Language (HTML) generated web-based forms, such as those for consumers making purchases or otherwise providing information on a data entry form via an Internet web page, and have limited usefulness beyond such applications.
Conventional data field population methods are unsuitable for datasets that embody extensible markup language (XML) grammars. XML is a standard data exchange format that allows different communities to define their own tags and attribute names. Current field population systems may not be utilized with sophisticated XML grammars, which contain nested composition and complex tree-like structures. These programs generally only support data that is relatively unsophisticated and linearly structured, and often require a perfect match between an incomplete document and the values and documents already stored to complete the incomplete document. As a result, current programs are not able to predict values for data fields unless there is constant repetition, no variability and a pre-stored perfect match. In contrast, XML data may be highly variable and may not be pre-stored. As a result XML documents require a high volume of manual data entry, which can be very labor intensive, time consuming and error-prone.
Consequently, it would be advantageous if a system and method existed to provide automated data entry of information supported by complex data structures.
USPTO Backgrounds
USPTO Backgrounds