My Account | Careers | Downloads | Blog

ABSTRACT:

All clustering methods have to assume some cluster relationship among the information objects that they are applied on. Similarity between a combine of objects will be defined either explicitly or implicitly. In this paper, we have a tendency to introduce a novel multi-viewpoint primarily based similarity measure and 2 connected clustering methods. The major distinction between a traditional dissimilarity/similarity live and ours is that the former uses solely a single viewpoint, that is that the origin, while the latter utilizes several different viewpoints, that are objects assumed to not be in the same cluster with the 2 objects being measured. Using multiple viewpoints, additional informative assessment of similarity could be achieved. Theoretical analysis and empirical study are conducted to support this claim. 2 criterion functions for document clustering are proposed based mostly on this new measure. We tend to compare them with many well-known clustering algorithms that use other popular similarity measures on numerous document collections to verify the advantages of our proposal.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Multi-View Clustering with the Cooperation of Visible and Hidden Views ABSTRACT: The use of multi-view data in real-world applications is becoming increasingly common, and as a result, numerous multi-view clustering
PROJECT TITLE : SCHAIN-IRAM: An Efficient and Effective Semi-Supervised Clustering Algorithm for Attributed Heterogeneous Information Networks ABSTRACT: A heterogeneous information network, also known as an HIN, is a network in
PROJECT TITLE : RDMN: A Relative Density Measure Based on MST Neighborhood for Clustering Multi-Scale Datasets ABSTRACT: Techniques for discovering intrinsic clusters that are based on density do so by classifying the regions
PROJECT TITLE : Fully Dynamic kk-Center Clustering With Improved Memory Efficiency ABSTRACT: Any machine learning library worth its salt will include both static and dynamic clustering algorithms as core components. The sliding
PROJECT TITLE : ESA-Stream: Efficient Self-Adaptive Online Data Stream Clustering ABSTRACT: A wide variety of big data applications generate an enormous amount of streaming data that is high-dimensional, real-time, and constantly

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry