Automated data entry system

Abstract

The present invention is a novel system and method for providing automated data entry of information. The system may include a processing subsystem capable of processing extensible markup language documents, a predicting subsystem capable of reviewing entered data of an input document and providing a suggestion to the input document, and a database for storing parsed extensible markup language documents. Database may maintain a plurality of relationships among received data of previous documents, and predictor may analyze a plurality of relationships for suggestions. The method for providing automated data entry of information may monitor received data, analyze relationships among received data, and predict a data entry field. A data entry field may be based on received data and relationships among received data. Predicting of data entry fields may incorporate a plurality of predictors whereby one or more values from values provided by each of the plurality of predictors is provided to a user.

1 . A system for automatic data entry of information, comprising:
 a processing subsystem, said processing subsystem being configured to receive documents and parse data entered in said documents;   a database, said database being configured to store parsed data, wherein a plurality of relationships developed from said parsed data is maintained; and   a predicting subsystem, said predicting subsystem being configured to review entered data of an input document and said plurality of relationships from received documents and provide a suggestion for an uncompleted field of said input document.   
   
   
       2 . The system as claimed in  claim 1 , wherein said documents are extensible markup language documents. 
   
   
       3 . The system as claimed in  claim 1 , wherein said processing subsystem parses data of a completed document and stores the parsed data of said completed document in said database. 
   
   
       4 . The system as claimed in  claim 1 , wherein said plurality of relationships developed from said parsed data includes node-value pairs and attribute-value pairs. 
   
   
       5 . The system as claimed in  claim 1 , wherein said predicting subsystem includes a plurality of individual predictors. 
   
   
       6 . The system as claimed in  claim 5 , wherein said plurality of individual predictors include at least one of a statistical predictor, an inductive predictor or an instance-based predictor. 
   
   
       7 . The system as claimed in  claim 6 , wherein said statistical predictor is a naïve Bayesian classifier. 
   
   
       8 . The system as claimed in  claim 6 , wherein said inductive predictor is a C4.5 inductive learning predictor. 
   
   
       9 . The system as claimed in  claim 6 , wherein said instance-based predictor is a K-Nearest-Neighbor predictor. 
   
   
       10 . The system as claimed in  claim 5 , wherein said predicting subsystem includes a suggestion aggregator. 
   
   
       11 . The system as claimed in  claim 10 , wherein said suggestion aggregator provides a single suggestion based upon a voting scheme among the plurality of predictors. 
   
   
       12 . The system as claimed in  claim 11 , wherein said predictor includes a weighting system. 
   
   
       13 . The system as claimed in  claim 12 , wherein said weighting system determines performance of each individual predictor of said plurality of individual predictors and weights votes of each individual predictor based upon past performance. 
   
   
       14 . The system as claimed in  claim 13 , wherein said weighting system assigns a weight to each individual predictor of a plurality of individual predictors based on a percentage of correctly provided suggestions of a total number of suggestions. 
   
   
       15 . The system as claimed in  claim 14 , wherein said weighting system adapts to multiple data domain types through adjustment of weighting for each individual predictor of said plurality of individual predictors based on past performance. 
   
   
       16 . The system as claimed in  claim 13 , wherein said suggestion aggregator provides a single suggestion based upon a voting scheme among the plurality of predictors in combination with weighting of each vote from each individual predictor. 
   
   
       17 . A data entry system for detecting errors in an input database comprising:
 a processing subsystem receiving one or more completed databases, the one or more completed databases storing parsed extensible markup language documents, and maintaining a plurality of relationships among received data of one or more previously received databases; and   a predicting subsystem reviewing an input database, checking entries of the input database, analyzing a plurality of relationships stored in the one or more databases to predict an entry for an input database, and providing one or more suggestions for a field where an error is detected.   
   
   
       18 . The system as claimed in  claim 17 , wherein said processing subsystem parses data of a completed document and transmits the parsed data of said completed document to said completed database. 
   
   
       19 . The system as claimed in  claim 17 , wherein said plurality of relationships among received data includes node-value pairs and attribute-value pairs. 
   
   
       20 . A method for checking errors in a database, comprising:
 monitoring received data from completed databases;   determining relationships among received data;   predicting an entry of said input database, wherein said entry of said input database is predicted based upon received data and relationships among received data;   detecting an error by comparing said predicted entry and an entered entry of said input database and, if the predicted entry matches the entered entry, determining the entered entry to be a correct entry or,   if the predicted entry does not match the entered entry, determining the entered entry to be an error;   providing an alert when said error is detected; and.   providing the predicted entry to said user for correction of said error.