Name
Title | ||
|---|---|---|
Relationship recommender system in a business and employment-oriented social network. |
Abstract | ||
|---|---|---|
In the last ten years, social networks have had a great influence on people’s lifestyles and have changed, above all, the way users communicate and relate. This is why, one of the main lines of research in the field of social networks focuses on finding and analyzing possible connections between users. These developments allow users to expand on their network of contacts without having to search among the total set of users. However, there are many types of social networks which attract users with specific needs, these needs influence on the type of contacts users are looking for. Our article proposes a relationship recommender system for a business and employment-oriented social network. The presented system functions by extracting relevant information from the social network which it then uses to adequately recommend new contacts and job offers to users. The recommender system uses information gathered from job offer descriptions, user profiles and users’ actions. Then, different metrics are applied in order to discover new ties that are likely to convert into relationships. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.ins.2017.12.050 | Information Sciences |
Keywords | Field | DocType |
Case-based reasoning,Recommender system,Social networks,Virtual organizations | Recommender system,World Wide Web,Social network,Artificial intelligence,Mathematics,Machine learning | Journal |
Volume | ISSN | Citations |
433 | 0020-0255 | 9 |
PageRank | References | Authors |
0.54 | 18 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pablo Chamoso | 1 | 94 | 24.80 |
| Alberto Rivas | 2 | 23 | 3.16 |
| Sara Rodríguez | 3 | 298 | 17.71 |
| Javier Bajo | 4 | 1451 | 118.96 |