By co-preserving hyperclique patterns during the clustering process, our experiments on real-world data sets show that better clustering results can be obtained ...

The duality between document and word clustering naturally leads to the consideration of storing the document dataset in a bipartite.

The claimed advantage of describing a document data set with a bipartite graph is that partitioning such a graph yields a co-clustering of words and documents.

Bibliographic details on Co-Clustering Bipartite with Pattern Preservation for Topic Extraction.

Oct 9, 2024 · This paper presents a novel and scalable co-clustering method designed to uncover intricate patterns in high-dimensional, large-scale datasets.

A new spectral co-clustering algorithm is used that uses the second left and right singular vectors of an appropriately scaled word-document matrix to yield ...

This paper describes a new bipartite formulation for word-document co-clustering such that hyperclique pat- terns, strongly affiliated documents in this ...

We present an innovative co-clustering algorithm that monotonically increases the preserved mutual informa- tion by intertwining both the row and column ...

Jun 25, 2017 · Co-clustering is the problem of deriving sub-matrices from the larger data matrix by simultaneously clustering rows and columns of the data ...

This paper describes a new bipartite formulation for word-document co-clustering such that hyperclique patterns, strongly affiliated documents in this case, ...