City vehicle social network community recommendation nearest optimal configuration method based on improved Steiner minimal tree

A technology of social network and optimal configuration, applied in the field of information sharing and dissemination of social recommendation in the social network of urban vehicles, to achieve good results

Inactive Publication Date: 2018-04-27
ZHEJIANG SCI-TECH UNIV
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  • Abstract
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Problems solved by technology

[0003] In the context of urban vehicular networks, limited by the limited wireless network of urban vehicular social networks, collabora

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  • City vehicle social network community recommendation nearest optimal configuration method based on improved Steiner minimal tree
  • City vehicle social network community recommendation nearest optimal configuration method based on improved Steiner minimal tree
  • City vehicle social network community recommendation nearest optimal configuration method based on improved Steiner minimal tree

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Embodiment Construction

[0022] In order to make the above and other objects, features and advantages of the invention more obvious, further description will be made below in conjunction with specific embodiments.

[0023] C 1 Each member in corresponds to an external trust value T ext,i , community C 2 Each member in the community C 1 Members in have an internal trust value T int,i (g, g). Then community C 1 to community C 2 The community recommendation near-optimal allocation problem in the urban vehicle social network can be defined as: in the community C 1 There exists at least one member in C that will be socially recommended, and then from members to C 2 The social recommendation path of members in is determined in order to maximize. Furthermore, it shows that the socially recommended optimal configuration has the highest confidence.

[0024] Community C 2 All members in will be included in all socially recommended configurations without the need to override C 1 All members in . For the

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Abstract

The invention discloses a near-optimal configuration method recommended by an urban vehicle social network community based on an improved Steiner minimum tree. In the urban vehicle social network, based on the existing efficient trust evaluation mechanism, the algorithm uses the individual external trust and internal trust evaluation model to study the optimal solution of social recommendation, which can effectively solve the optimal configuration of social recommendation in the urban vehicle social network community NP‑hard problem. Moreover, compared with the existing optimal algorithm (Optimal Algorithm, OA) and greedy algorithm (Greedy Algorithm, GA), the ANOCSR algorithm can achieve better results in terms of output reliability and average execution time performance. There are notable applications in the area of ​​communication and sharing and driver's decision-making.

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Claims

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Application Information

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Owner ZHEJIANG SCI-TECH UNIV
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