Friendship Recommendation System based on a Social Network Topological Analysis
Friendship Recommendation System based on a Social Network Topological Analysis
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| Short Description: | Our work tries to define and apply several automatic methodology for creating a Friendship Recommendation System inside an Online Social Network. |
| Coordinator: | MarcoColombetti (colombet@elet.polimi.it) |
| Tutor: | DavidLaniado (david.laniado@gmail.com), RiccardoTasso (tasso@elet.polimi.it) |
| Collaborator: | |
| Students: | MicheleMonti (michimonti@tiscali.it) |
| Research Area: | Social Software and Semantic Web |
| Research Topic: | Social Network Analysis |
| Start: | 2009/07/27 |
| End: | 2010/05/03 |
| Status: | Active |
| Level: | Ms |
| Type: | Thesis |
Contents
Part 1: project profile
Project name
Friendship Recommendation System based on a Social Network Topological Analysis
Project short description
Our work tries to define and apply several automatic methodology for creating a Friendship Recommendation System inside an Online Social Network.
Dates
- Start date: 2009/07/27
- End date: 2010/05/03
People involved
Project head(s)
- Prof. Marco Colombetti
Other Politecnico di Milano people
- Ing. David Laniado
- Ing. Riccardo Tasso
Students worked on the thesis
Part 2: project description
With the rising of Web 2.0, evolution of the traditional static Web born with the advent of Internet, that comprised only pages defined without interaction between the virtual world and the physical Person, Social Network online are being more and more diffused. They allow, with virtual ties of friendship which the Persons, to find again themselves like which are really in the life every day.
This job of Thesis provides to model techniques for create Friendship Recommendation for an active customer in a Social Network, and it is based on three fundamental supports:
- The collection of the Candidates To suggest;
- The generation of the Personal Network of the customer on which it is wanted to be carried out the analysis;
- The construction of the Ranking through using five metrics based on Topological analysis of a net. All this has been thought before from a theoretical point of view and then implemented through different Modules Software that render all automated.
