Detecting Communities in Heterogeneous Multi-Relational Networks:A Message Passing based Approach Article Swipe
Maoying Qiao
,
Jun Yu
,
Wei Bian
,
Dacheng Tao
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2004.02842
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2004.02842
Community is a common characteristic of networks including social networks, biological networks, computer and information networks, to name a few. Community detection is a basic step for exploring and analysing these network data. Typically, homogenous network is a type of networks which consists of only one type of objects with one type of links connecting them. There has been a large body of developments in models and algorithms to detect communities over it. However, real-world networks naturally exhibit heterogeneous qualities appearing as multiple types of objects with multi-relational links connecting them. Those heterogeneous information could facilitate the community detection for its constituent homogeneous networks, but has not been fully explored. In this paper, we exploit heterogeneous multi-relational networks (HMRNet) and propose an efficient message passing based algorithm to simultaneously detect communities for all homogeneous networks. Specifically, an HMRNet is reorganized into a hierarchical structure with homogeneous networks as its layers and heterogeneous links connecting them. To detect communities in such an HMRNet, the problem is formulated as a maximum a posterior (MAP) over a factor graph. Finally a message passing based algorithm is derived to find a best solution of the MAP problem. Evaluation on both synthetic and real-world networks confirms the effectiveness of the proposed method.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2004.02842
- https://arxiv.org/pdf/2004.02842
- OA Status
- green
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3014367856
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3014367856Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2004.02842Digital Object Identifier
- Title
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Detecting Communities in Heterogeneous Multi-Relational Networks:A Message Passing based ApproachWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2020Year of publication
- Publication date
-
2020-04-06Full publication date if available
- Authors
-
Maoying Qiao, Jun Yu, Wei Bian, Dacheng TaoList of authors in order
- Landing page
-
https://arxiv.org/abs/2004.02842Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2004.02842Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2004.02842Direct OA link when available
- Concepts
-
Computer science, Message passing, Data science, Distributed computing, Theoretical computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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51Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.including | 7 |
| abstract_inverted_index.naturally | 76 |
| abstract_inverted_index.networks, | 9, 11, 15, 103 |
| abstract_inverted_index.networks. | 134 |
| abstract_inverted_index.posterior | 170 |
| abstract_inverted_index.qualities | 79 |
| abstract_inverted_index.structure | 143 |
| abstract_inverted_index.synthetic | 196 |
| abstract_inverted_index.Evaluation | 193 |
| abstract_inverted_index.Typically, | 33 |
| abstract_inverted_index.algorithms | 67 |
| abstract_inverted_index.biological | 10 |
| abstract_inverted_index.connecting | 54, 89, 153 |
| abstract_inverted_index.facilitate | 95 |
| abstract_inverted_index.formulated | 165 |
| abstract_inverted_index.homogenous | 34 |
| abstract_inverted_index.real-world | 74, 198 |
| abstract_inverted_index.communities | 70, 130, 157 |
| abstract_inverted_index.constituent | 101 |
| abstract_inverted_index.homogeneous | 102, 133, 145 |
| abstract_inverted_index.information | 14, 93 |
| abstract_inverted_index.reorganized | 139 |
| abstract_inverted_index.developments | 63 |
| abstract_inverted_index.hierarchical | 142 |
| abstract_inverted_index.Specifically, | 135 |
| abstract_inverted_index.effectiveness | 202 |
| abstract_inverted_index.heterogeneous | 78, 92, 115, 151 |
| abstract_inverted_index.characteristic | 4 |
| abstract_inverted_index.simultaneously | 128 |
| abstract_inverted_index.multi-relational | 87, 116 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |