Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph
To solve the problem in measuring the similarity of heterogeneous information networks, a similarity measuring algorithm was proposed. It calculates the difference between the maximum common sub-graph and minimum common hyper-graph, based on feature sub-graph of the current node. The algorithm takes...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2014-11-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2014.11.012/ |
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| _version_ | 1841529399529177088 |
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| author | Biao Zhang Chuan Li Hongyu Xu Yanmei Li Ning Yang Qian Luo |
| author_facet | Biao Zhang Chuan Li Hongyu Xu Yanmei Li Ning Yang Qian Luo |
| author_sort | Biao Zhang |
| collection | DOAJ |
| description | To solve the problem in measuring the similarity of heterogeneous information networks, a similarity measuring algorithm was proposed. It calculates the difference between the maximum common sub-graph and minimum common hyper-graph, based on feature sub-graph of the current node. The algorithm takes graph theory as its foundation, set different weight to different kinds of edges, considers nodes information as well as graph to topological information, and makes full use of the information in heterogeneous network. The result shows that the proposed algorithm has wonderful effectiveness and efficiency. |
| format | Article |
| id | doaj-art-27cbe52fd355475185a0c58bef107ba7 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2014-11-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-27cbe52fd355475185a0c58bef107ba72025-01-15T03:18:04ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012014-11-0130667259617517Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-GraphBiao ZhangChuan LiHongyu XuYanmei LiNing YangQian LuoTo solve the problem in measuring the similarity of heterogeneous information networks, a similarity measuring algorithm was proposed. It calculates the difference between the maximum common sub-graph and minimum common hyper-graph, based on feature sub-graph of the current node. The algorithm takes graph theory as its foundation, set different weight to different kinds of edges, considers nodes information as well as graph to topological information, and makes full use of the information in heterogeneous network. The result shows that the proposed algorithm has wonderful effectiveness and efficiency.http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2014.11.012/heterogeneous information networkgraph similaritysimilarity measurementfeature sub-graph |
| spellingShingle | Biao Zhang Chuan Li Hongyu Xu Yanmei Li Ning Yang Qian Luo Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph Dianxin kexue heterogeneous information network graph similarity similarity measurement feature sub-graph |
| title | Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph |
| title_full | Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph |
| title_fullStr | Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph |
| title_full_unstemmed | Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph |
| title_short | Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph |
| title_sort | heterogeneous information networks node similarity measurement based on feature sub graph |
| topic | heterogeneous information network graph similarity similarity measurement feature sub-graph |
| url | http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2014.11.012/ |
| work_keys_str_mv | AT biaozhang heterogeneousinformationnetworksnodesimilaritymeasurementbasedonfeaturesubgraph AT chuanli heterogeneousinformationnetworksnodesimilaritymeasurementbasedonfeaturesubgraph AT hongyuxu heterogeneousinformationnetworksnodesimilaritymeasurementbasedonfeaturesubgraph AT yanmeili heterogeneousinformationnetworksnodesimilaritymeasurementbasedonfeaturesubgraph AT ningyang heterogeneousinformationnetworksnodesimilaritymeasurementbasedonfeaturesubgraph AT qianluo heterogeneousinformationnetworksnodesimilaritymeasurementbasedonfeaturesubgraph |