Trigger Files Text Analysis and Processing Time Anomaly Detection

Abstract

Today the data processing is a vital part of the system supporting organization processes and transactions. A lot of data is managed, transmitted and stored daily. The format of the data is structured, unstructured or semi structured. Information Technology researchers are all in agreement that unstructured data is at least 80 percent of all enterprise data. It is unrealistic to expect that data will be perfect. The unstructured data hides important, when it is analyzed will aid businesses to have better decisions. The proposal of this project is an application using machine learning techniques like, information retrieval, data mining, and text mining with the intention to find possible anomalous values or processing time delays in the archived trigger files corpus. Key Terms - Data Mining, Machine Learning, Text Mining, Trigger File.