Green Information Extraction from Family Books

Abstract

There is rising demand for the retrieval of genealogical information from semi-structured books. Nuggets of personal interest are currently transcribed piecemeal by volunteers. GreenBook is an effective alternative for recovering most of the desired information from any of the hundreds of thousands of books of ancestral records that have already been scanned and digitized. It minimizes human intervention by letting the user benefit from automatically compiled statistics from the book, and lets computer search benefit from user insights. GreenBook combines enhanced template matching with spreadsheet-based interaction for the rapid specification of the text to be extracted. The accuracy and completeness of the extracted information are limited only by the user's stamina. About 3 h of user interaction yielded 99% precision and 97% recall on books of Scottish birth and marriage records, Ohio funeral home records, and a family history spanning 300 years. The system is designed to facilitate transition to new books.

An Experimental Study of Diversity of Diabetes Disease Features by Bagging and Boosting Ensemble Method with Rule Based Machine Learning Classifier Algorithms

“…Accuracy measures the performance of the algorithms and precision recognized pattern as positive predictive value (Table 2). Recall measures actual positive value in real requires facility while F1-Score provide balance between precision and recall [18]. TP = True Positive, TN = True Negative, FP = False positive and FN = False Negative…”