TrustDL: Use of trust-based dictionary learning to facilitate recommendation in social networks

peer reviewedCollaborative filtering (CF) is a widely applied method to perform recommendation tasks in a wide range of domains and applications. Dictionary learning (DL) models, which are highly important in CF-based recommender systems (RSs), are well represented by rating matrices. However, these methods alone do not resolve the cold start and data sparsity issues in RSs. We observed a significant improvement in rating results by adding trust information on the social network. For that purpose, we proposed a new dictionary learning technique based on trust information, called TrustDL, where the social network data were employed in the process of recommendation based on structural details on the trusted network. TrustDL sought to integrate the sources of information, including trust statements and ratings, into the recommendation model to mitigate both problems of cold start and data sparsity. It conducted dictionary learning and trust embedding simultaneously to predict unknown rating values. In this paper, the dictionary learning technique was integrated into rating learning, along with the trust consistency regularization term designed to offer a more accurate understanding of the feature representation. Moreover, partially identical trust embedding was developed, where users with similar rating sets could cluster together, and those with similar rating sets could be represented collaboratively. The proposed strategy appears significantly beneficial based on experiments conducted on four frequently used datasets: Epinions, Ciao, FilmTrust, and Flixster

Two collaborative filtering recommender systems based on sparse dictionary coding

The design and analysis of a novel wideband, monolithic, bandpass, π-network, voltage controlled attenuator (VCA) is presented. A 24 to 32 GHz VCA was developed using 0.15μm GaAs pHEMT technology. This is the first reported VCA to use a bandpass filter topology to achieve the required operating frequency band and eliminate the effects of parasitic capacitances of the pHEMTs. The bandpass filter absorbs the parasitic capacitances and thereby eliminates their detrimental effects. The measured attenuation dynamic range is 12dB ± 0.5dB with minimum insertion loss of 2-3dB. The input power handling capability is up to 0dBm. The VCA is well matched and may be placed in a 50Ω system [1]