Improved Text Mining Algorithm for Fault Detection using Combined D-Matrix
Ashish P. Ramdasi1, K. M. Mehata2
1Ashish P. Ramdasi*, Hindustan Institute of Technology and Science, Padur, Chennai. India.
2K. M. Mehata, Hindustan Institute of Technology and Science, Padur, Chennai, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1376-1369 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7309118419/2019©BEIESP | DOI: 10.35940/ijrte.D7309.118419

Open Access | Ethics and Policies | Cite  | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Systematic diagnostic version of Fault dependency (D-matrix) mostly use for setup the fault method records and its contributing courting on the classified system-degree. It includes dependencies and association between recognizable failure approaches and signs and symptoms related to a machine. Proposed system in this paper describes an relations of domain primarily based textual content repository for construction and renovate combined data dependency matrix through mining lacks of the tuple exact unstructured text ,cumulative during the analysis incidents. Here paradigm is combined D matrix and then fault analysis through textual content mining using advance data preprocessing technique approach to pick out dependencies. Using real-existence statistics accumulated and validated in proposed method.
Keywords: Combine D-Matrix, Text Preprocessing, Fault Analysis, Unstructured Data.
Scope of the Article: Text Mining.