Data structure for representing a graph: combination of linked list and hash table Export

@article{citeulike:5629943, abstract = {In this article we discuss a data structure, which combines advantages of two different ways for representing graphs: adjacency matrix and collection of adjacency lists. This data structure can fast add and search edges (advantages of adjacency matrix), use linear amount of memory, let to obtain adjacency list for certain vertex (advantages of collection of adjacency lists). Basic knowledge of linked lists and hash tables is required to understand this article. The article contains examples of implementation on Java.}, archivePrefix = {arXiv}, author = {Kolosovskiy, Maxim A.}, citeulike-article-id = {5629943}, citeulike-linkout-0 = {http://arxiv.org/abs/0908.3089}, citeulike-linkout-1 = {http://arxiv.org/pdf/0908.3089}, day = {21}, eprint = {0908.3089}, keywords = {computation, data-structures}, month = {Aug}, posted-at = {2009-08-24 20:03:03}, priority = {2}, title = {Data structure for representing a graph: combination of linked list and hash table}, url = {http://arxiv.org/abs/0908.3089}, year = {2009} }

TY - JOUR ID - citeulike:5629943 L3 - citeulike-article-id:5629943 N2 - In this article we discuss a data structure, which combines advantages of two different ways for representing graphs: adjacency matrix and collection of adjacency lists. This data structure can fast add and search edges (advantages of adjacency matrix), use linear amount of memory, let to obtain adjacency list for certain vertex (advantages of collection of adjacency lists). Basic knowledge of linked lists and hash tables is required to understand this article. The article contains examples of implementation on Java. TI - Data structure for representing a graph: combination of linked list and hash table KW - computation KW - data-structures AU - Kolosovskiy, Maxim PY - 2009/Aug/21/ UR - http://arxiv.org/abs/0908.3089 ER -