• Kaveri M. More
• Prof. R. P. Dahake

Clustering is very effective tool developed for two dimensional co-occurrences as well as bipartite data. There is need of significant computational resources for huge data processing. Traditional approaches of co-clustering suffered from issues of graph partitioning. Expectation-maximization (EM) algorithms such as, k-means clustering algorithms gives the provable evidence with the sequential updates. Without affecting result it reduces computational cost, therefore updates in the sequential manner in a distributed environment can be propose by using AMCC algorithms and by dividing clusters and batch updates approaches. AMCC algorithms can prove efficiency of Co-Clustering. The proposed work can also contributes attribute based filtering of input dataset.

Co-Clustering, concurrent updates, sequential updates, cloud computing, distributed framework

"Review on Clustering of Documents with Sequential Update in Distributed Environment", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.108-112, June-2018, Available :http://www.jetir.org/papers/JETIR1806016.pdf

"Review on Clustering of Documents with Sequential Update in Distributed Environment", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp108-112, June-2018, Available at : http://www.jetir.org/papers/JETIR1806016.pdf