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Efficient D-Matrix construction strategy for Unstructured Text Mining using FDD

Publication Date : 10/07/2015

Author(s) :

Swati S Hinge , B. R. Nandwalkar.

Conference Name :
4th International Conference on Recent Trends in Engineering & Technology(ICRTET-2015) July 2-4,2015 Organized by SNJB's KBJ College of Engineering,Chandwad,Nashik,Maharashtra,India

Abstract :

The term text mining is to perform operation on unstructured (text) information, from the noisy text extract meaningful text data (information), and thus make sure that the information consist in the text available to the various data mining. There is necessity to collect information regarding various symptoms and failure modes to alter the fault dependency matrix which can be helpful to construct correct and efficient fault diagnosis. To decrease the system’s downtime the fault detection and diagnosis (FDD) is performed to detect the faults and diagnose the root-causes. In process of engineering Fault detection and diagnosis is an important issue. In proposed system, we initially develop the fault diagnosis ontology of attributes and relationships with it observed in the fault diagnosis database. Next, we construct the algorithms of text mining which will use of the ontology to identify the important artifacts from the unstructured repair verbatim text which is online as well as offline.

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