In this paper, we design the hybrid clustering algorithms, which involve two level clustering. At each of the levels, users can select the k-means, hierarchical or SOM clustering techniques. Unlike the existing cluster analysis techniques, the hybrid clustering approach developed here represents the original data set using a smaller set of prototype vectors (cluster means), which allows efficie...

We propose a new hybrid clustering framework to incorporate text mining with bibliometrics in journal set analysis.The framework integrates two different approaches: clustering ensemble and kernel-fusion clustering. To improve the flexibility and the efficiency of processing large-scale data, we propose an information-based weighting scheme to leverage the effect of multiple data sources in hyb...

This paper presents a hybrid approach for clustering based on particle swarm optimization (PSO) and bacteria foraging algorithms (BFA). The new method AutoCPB (Auto-Clustering based on particle bacterial foraging) makes use of autonomous agents whose primary objective is to cluster chunks of data by using simplistic collaboration. Inspired by the advances in clustering using particle swarm opti...

Information retrieval is one of the major research areas due to accumulation of huge information in digital form. Various techniques of Information retrieval are based on the fact that various terms present in a document along with their frequency of occurrence signify the semantics of the document. Recent attempts to find the relevant document for a context represents documents in a Latent Sem...

Clustering is a discovering process of meaningful intbrmation by grouping similar data into compact clusters. Most of traditional clustering methods are in favor of small datasets and have difficulties handling very large datasets. They are not adequate clustering methods for partitioning huge datasets in data mining perspective. We propose a new clustering technique, HRC(hierarchical represent...

Recommender system is a kind of web intelligence techniques to make a daily information filtering for people. In this work1, Clustering techniques have been applied to the item-based collaborative filtering framework to solve the cold start problem. It also suggests a way to integrate the content information into the collaborative filtering. Extensive experiments have been conducted on MovieLen...

In the last years, new clustering approaches utilizing the notion of multiple clusterings have gained attention. Two general directions — each with its individual benefits — are identifiable: (i) extraction of multiple alternative clustering solutions from one dataset and (ii) combination of multiple clusterings of a dataset into one robust consensussolution. In this paper, we propose a novel h...

Text Clustering is a text mining technique which is used to group similar documents into single cluster by using some sort of similarity measure and placing dissimilar documents into different clusters. Most of the popular clustering algorithms treats document as conglomeration of words and do not consider the syntactic or semantic relations between words. To overcome this drawback, some algori...