An empirical comparative analysis of clustering algorithms for big data applications

• Main Author: Delos Santos, Duke Danielle T.
• Format: text
• Language: English
• Published: Animo Repository 2017
• Subjects: Big data; Algorithms
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/5395
• Institution: De La Salle University

Big data is a vaguely defined term that describes a dataset as either too large or too complex to analyze and get satisfactory results. Clustering algorithms are a possible solution to this problem of big data, where they can be categorized according to one or more of three clustering objectives. Th...