Dr. P. Perumal
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Dr. P. Perumal

Professor
Department of Computer Science and Engineering (UG), Sri Ramakrishna Engineering College, India


Highest Degree
Ph.D. in Information and Communication Engineering from Anna University, Chennai, India

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Area of Interest:

Computer Sciences
100%
Data Mining
62%
Image Processing
90%
Information Technology
75%
Software Engineering
55%

Research Publications in Numbers

Books
0
Chapters
0
Articles
25
Abstracts
23

Selected Publications

  1. Indumathi, A. and P. Perumal, 2018. Improved text mining for bulk data using deep learning approach. Int. J. Comput. Sci. Inform. Security, 16: 251-254.
  2. Swathi, V., S.S. Kumar and P. Perumal, 2017. A novel fuzzy-bayesian classification method for automatic text categorization. Int. J. Scient. Res. Sci. Technol., 2: 233-239.
    Direct Link  |  
  3. Sowmiya, H. and P. Perumal, 2017. Traffic aware partitioning and aggregation using map reduce with data security. Int. J. Pure Applied Math., 115: 629-635.
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  4. Pitchandi, P., S. Muthukumaravel and S. Boopathy, 2016. Content based segregation of pertinent documents using adaptive progression. Circuits Syst., 7: 1856-1865.
    CrossRef  |  Direct Link  |  
  5. Perumal, P., M.S.G. Devasena and R. Ramya, 2016. Enhanced filter based personalized semantic search. Asian J. Inform. Technol., 15: 4844-4850.
    CrossRef  |  Direct Link  |  
  6. Perumal, P. and N.A. Reddy, 2015. Data aware query suggestion by user click through feedback. Int. J. Contemp. Res. Comput. Sci. Technol., 1: 15-20.
  7. Perumal, P. and M. Kasthuri, 2015. A survey on opinion mining from online review sentences. Int. Res. J. Eng. Technol., 2: 1183-1189.
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  8. Perumal, P. and D. Anandhu, 2015. Video search reranking via cross reference based fusion strategy. Int. J. Trend Res. Dev., 2: 22-29.
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  9. Perumal, P., R. Nedunchezhian and C. Gomathi, 2013. An enhanced document clustering approach using optimization algorithm. Int. J. Res. Eng. Adv. Technol., 1: 1-7.
  10. Perumal, P. and R. Nedunchezhian, 2012. MLK-means-A hybrid machine learning based k-means clustering algorithm for document clustering. Int. J. Comput. Sci. Issues, 9: 282-293.
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  11. Perumal, P. and R. Nedunchezhian, 2012. Concept based document similarity based on suffix tree document clustering. Int. J. Comput. Sci. Eng. Technol., 3: 470-475.
  12. Perumal, P. and R. Nedunchezhian, 2012. An improved hybrid K-means clustering algorithm using machine learning and von-mises-fisher method for document clustering. Wulfenia J., 19: 51-72.
  13. Perumal, P., R. Nedunchezhian and D. Brindha, 2011. An empirical selection method for document clustering. Int. J. Comput. Applic., 31: 15-19.
    Direct Link  |  
  14. Perumal, P. and R. Nedunchezhian, 2011. Performance evaluation of three model-based documents clustering algorithms. Eur. J. Scient. Res., 52: 618-629.
  15. Perumal, P. and R. Nedunchezhian, 2011. Performance analysis of standard k-means clustering algorithm on clustering TMG format document data. Int. J. Comput. Applic. Eng. Sci., 1: 406-412.
  16. Perumal, P. and R. Nedunchezhian, 2011. Improving the performance of multivariate Bernoulli model based document clustering algorithms using transformation techniques. J. Comput. Sci., 7: 762-769.