A New Reduction from Search SVP to Optimization SVP

It is well known that search SVP is equivalent to optimization SVP. However, the former reduction from search SVP to optimization SVP by Kannan needs polynomial times calls to the oracle that solves the optimization SVP. In this paper, a new rank-preserving reduction is presented with only one call to the optimization SVP oracle. It is obvious that the new reduction needs the least calls, and improves Kannan's classical result. What's more, the idea also leads a similar direct reduction from search CVP to optimization CVP with only one call to the oracle

Multiangle social network recommendation algorithms and similarity network evaluation

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