Multiangle social network recommendation algorithms and similarity network evaluation

Jinyu Hu, Zhiwei Gao, Weisen Pan

Research output: Contribution to journalArticlepeer-review

62 Citations (Scopus)
3 Downloads (Pure)

Abstract

Multiangle social network recommendation algorithms (MSN) and a new assessmentmethod, called similarity network evaluation (SNE), are both proposed. From the viewpoint of six dimensions, the MSN are classified into six algorithms, including user-based algorithmfromresource point (UBR), user-based algorithmfromtag point (UBT), resource-based algorithm fromtag point (RBT), resource-based algorithm from user point (RBU), tag-based algorithm from resource point (TBR), and tag-based algorithm from user point (TBU). Compared with the traditional recall/precision (RP) method, the SNE is more simple, effective, and visualized. The simulation results show that TBR and UBR are the best algorithms, RBU and TBU are the worst ones, and UBT and RBT are in the medium levels.
Original languageEnglish
Pages (from-to)248084
JournalJournal of Applied Mathematics
Volume2013
DOIs
Publication statusPublished - Jul 2013

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