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EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

Existing system in co-clustering has recently received a lot of attention due to its effectiveness in simultaneously partitioning words and documents by exploiting the relationships between them.

However, most of the existing co-clustering methods neglect or only partially reveal the interword and interdocument relationships

PROPOSED CONCEPT:-

The Proposed system the word-document relationship is modeled by following information-theoretic co-clustering (ITCC).

The local consistency on both interword and interdocument relationships is revealed by a local predictor; and the global consistency on both interword and interdocument relationships is explored.

EXISTING METHODS:-

Co-clustering

PROPOSED TECHNIQUE:-         

Co-clustering via local and global consistency(CCLGC)

TECHNIQUE DEFNITION:-

Model word-document relationships by the edges between words. Word-document contingency table as an empirical joint probability distribution of two random variables, respectively, and matrix factorization-based co-clustering methods reconstruction.

TECHNIQUE DEFNITION:-

To fully explore the word-document relationship as well as the interword and interdocument relationships in terms of both local regions and global data manifold. The basic idea is to incorporate the combination of local and global regularization.

DRAWBACKS:-

Fitting loss with sum of absolute error noise.

Interword and interdocument relationships, but not fully discover them.

ADVANTAGES:-

Local and global regularization into clustering

and achieved good performance.

No constraint on effective between all word and documents.