iTrace: An Implicit Trust Inference Method for Trust-aware Collaborative Filtering

The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. A collaborative filtering (CF) algorithm recommends items of interest to the target user by leveraging the votes given by other similar users. In a standard CF framework, it is assumed that the credibility of every voting user is exactly the same with respect to the target user. This assumption is not satisfied and thus may lead to misleading recommendations in many practical applications. A natural countermeasure is to design a trust-aware CF (TaCF) algorithm, which can take account of the difference in the credibilities of the voting users when performing CF. To this end, this paper presents a trust inference approach, which can predict the implicit trust of the target user on every voting user from a sparse explicit trust matrix. Then an improved CF algorithm termed iTrace is proposed, which takes advantage of both the explicit and the predicted implicit trust to provide recommendations with the CF framework. An empirical evaluation on a public dataset demonstrates that the proposed algorithm provides a significant improvement in recommendation quality in terms of mean absolute error (MAE).Comment: 6 pages, 4 figures, 1 tabl

Thermal spin-transfer in Fe-MgO-Fe tunnel junctions

We compute thermal spin transfer torques (TST) in Fe-MgO-Fe tunnel junctions using a first principles wave function-matching method. At room temperature, the TST in a junction with 3 MgO monolayers amounts to 10^-7J/m^2/K, which is estimated to cause magnetization reversal for temperature differences over the barrier of the order of 10 K. The large TST can be explained by multiple scattering between interface states through ultrathin barriers. The angular dependence of the TST can be very skewed, possibly leading to thermally induced high-frequency generation.Comment: 5 pages, 5 figure

The Influence of Creativity-Relevant Skill on Creativity —— A Moderated Mediation Model

Employee creativity is very important for enhancing enterprise innovation ability to seize the opportunity in fierce competition. Based on the componential theory of creativity, this paper explores the influence of creativity-relevant skills on creativity through the transmission mechanism with Chinese characteristics. It has been found that creativity-relevant skills promote creativity has a dual path by enhancing creativity role identification and weakening mental transformation costs. At the same time, creative job requirement not only significantly regulate the positive and negative relationship between creativity role identity, mental transformation costs and creativity, but also significantly moderated the mediating effect of creativity-relevant skills on creativity through creative role identity and mental transformation costs. Managers should clarify the mechanism and focus on improving their creativity-relevant skills, so as to enhance their overall innovation capability. Keywords: creativity-relevant skills; creativity role identity; mental transformation costs; creative job requirement; creativit