  Information overload is a serious problem in modern society and many
solutions such as recommender system have been proposed to filter out
irrelevant information. In the literature, researchers mainly dedicated to
improve the recommendation performance (accuracy and diversity) of the
algorithms while overlooked the influence of topology of the online user-object
bipartite networks. In this paper, we find that some information provided by
the bipartite networks is not only redundant but also misleading. With such
"less can be more" feature, we design some algorithms to improve the
recommendation performance by eliminating some links from the original
networks. Moreover, we propose a hybrid method combining the time-aware and
topology-aware link removal algorithms to extract the backbone which contains
the essential information for the recommender systems. From the practical point
of view, our method can improve the performance and reduce the computational
time of the recommendation system, thus improve both of their effectiveness and
efficiency.
