### Abstract

In this work, K-partitioning of signed or weighted bipartite graph problem has been introduced, which appears as a real life problem where the partitions of bipartite graph represent two different entities and the edges between the nodes of the partitions represent the relationships among them. A typical example is the set of people and their opinions, whose strength is represented as signed numerical values. Using the weights on the edges, these bipartite graphs can be partitioned into two or more clusters. In political domain, a cluster represents strong relationship among a group of people and a group of issues. In the paper, we formally define the problem and compare different heuristics, and show through both real and simulated data the effectiveness of our approaches.

Original language | English (US) |
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Title of host publication | Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013 |

Pages | 815-820 |

Number of pages | 6 |

DOIs | |

State | Published - 2013 |

Event | 2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013 - Washington, DC, United States Duration: Sep 8 2013 → Sep 14 2013 |

### Other

Other | 2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013 |
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Country | United States |

City | Washington, DC |

Period | 9/8/13 → 9/14/13 |

### Keywords

- Bipartite graphs
- Graph partitioning
- Social networks

### ASJC Scopus subject areas

- Software

### Cite this

*Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013*(pp. 815-820). [6693419] https://doi.org/10.1109/SocialCom.2013.122

**K-partitioning of signed or weighted bipartite graphs.** / Omeroglu, Nurettin B.; Toroslu, Ismail H.; Gokalp, Sedat; Davulcu, Hasan.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013.*, 6693419, pp. 815-820, 2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013, Washington, DC, United States, 9/8/13. https://doi.org/10.1109/SocialCom.2013.122

}

TY - GEN

T1 - K-partitioning of signed or weighted bipartite graphs

AU - Omeroglu, Nurettin B.

AU - Toroslu, Ismail H.

AU - Gokalp, Sedat

AU - Davulcu, Hasan

PY - 2013

Y1 - 2013

N2 - In this work, K-partitioning of signed or weighted bipartite graph problem has been introduced, which appears as a real life problem where the partitions of bipartite graph represent two different entities and the edges between the nodes of the partitions represent the relationships among them. A typical example is the set of people and their opinions, whose strength is represented as signed numerical values. Using the weights on the edges, these bipartite graphs can be partitioned into two or more clusters. In political domain, a cluster represents strong relationship among a group of people and a group of issues. In the paper, we formally define the problem and compare different heuristics, and show through both real and simulated data the effectiveness of our approaches.

AB - In this work, K-partitioning of signed or weighted bipartite graph problem has been introduced, which appears as a real life problem where the partitions of bipartite graph represent two different entities and the edges between the nodes of the partitions represent the relationships among them. A typical example is the set of people and their opinions, whose strength is represented as signed numerical values. Using the weights on the edges, these bipartite graphs can be partitioned into two or more clusters. In political domain, a cluster represents strong relationship among a group of people and a group of issues. In the paper, we formally define the problem and compare different heuristics, and show through both real and simulated data the effectiveness of our approaches.

KW - Bipartite graphs

KW - Graph partitioning

KW - Social networks

UR - http://www.scopus.com/inward/record.url?scp=84893520959&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893520959&partnerID=8YFLogxK

U2 - 10.1109/SocialCom.2013.122

DO - 10.1109/SocialCom.2013.122

M3 - Conference contribution

AN - SCOPUS:84893520959

SN - 9780769551371

SP - 815

EP - 820

BT - Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013

ER -