Extracto
TABLE OF CONTENTS
Chapter 1: Introduction
1.1 Clustering
1.2 Types of Clustering
1.3 Classification of Clustering Algorithms
1.4 Requirements of Clustering
1.5 Stages in Clustering
1.6 Different Types of Clusters
1.7 Different Types of Clustering Algorithms
1.8 Applications of Clustering
1.9 Web Clustering Engines
Chapter 2: Literature Survey
Chapter 3: Tools and Technologies
3.1 System Requirements
3.2 System Environment
Chapter 4: Problem Description
4.1 Existing System
4.2 Objective
4.2.1 HACM Clustering Algorithm and its Shortcomings
4.2.2 K-Means Clustering Algorithm and its Advantages over HACM
4.3 Proposed System
Chapter 5: System Design
5.1 System Architecture
Chapter 6: Conclusion and Future Work
References
Final del extracto de 55 páginas
- Citar trabajo
- Priyanka Nandal (Autor), 2020, Optimizing Web Search Results for Image. K-means Clustering Algorithm, Múnich, GRIN Verlag, https://www.grin.com/document/983236
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