Partitioning §

Group: 4 #group-4

Relations §

• Fragmentation: Fragmentation involves partitioning or dividing something into distinct parts or segments.
• Matrix Partitioning: Matrix partitioning divides a large matrix into smaller, more manageable sub-matrices or partitions.
• Dissection: Partitioning can involve dissecting or cutting apart a whole into its constituent parts.
• Gerrymandering: Gerrymandering is the practice of partitioning electoral districts to favor a particular political party or group.
• Decomposition: Partitioning decomposes a larger whole into smaller components or parts.
• Divide: Partitioning involves dividing a whole into parts or portions.
• Distributed Systems: Data and workloads are partitioned across multiple nodes in distributed systems for scalability.
• Network Partitioning: Network partitioning divides a computer network into smaller, isolated segments or partitions.
• Database Sharding: Database sharding is a partitioning technique used to distribute data across multiple databases or servers.
• Sectioning: Partitioning involves sectioning or dividing something into distinct sections or parts.
• Fragmentation: Partitioning can lead to fragmentation, where a whole is broken into smaller fragments.
• Subdivision: Partitioning involves subdividing a whole into smaller parts.
• Grouping: Partitioning is the act of dividing a set of items into non-overlapping groups or partitions.
• Compartmentalization: Partitioning compartmentalizes or divides a larger entity into separate compartments or sections.
• Disk Partitioning: Disk partitioning divides a hard disk drive into multiple logical partitions or sections.
• Graph Partitioning: Graph partitioning involves dividing the vertices of a graph into smaller, disjoint sets or partitions.
• Separate: Partitioning separates a larger entity into smaller, distinct units.
• Segment: Partitioning segments a larger whole into smaller segments or sections.
• Partitional Clustering: Partitional clustering is a technique used in data mining and machine learning to partition data into distinct clusters.
• Segmentation: Segmentation involves partitioning data into distinct, non-overlapping groups or segments.
• Disintegration: In some cases, partitioning can lead to the disintegration or breaking apart of a whole.
• Split: The process of partitioning splits a whole into multiple parts.
• Classification: Classification partitions or divides a set of things into subsets or classes.
• Portion: Partitioning divides something into portions or shares.