Estimating Trust Strength For Supporting Effective Recommendation Services

In the age of information explosion, Internet facilitates product searching and collecting much more convenient for users. However, it is time-consuming and exhausting for users to deal with large amounts of product information. In response, various recommendation approaches have been developed to recommend products that match users’ preferences and requirements. In addition to the well-known collaborative filtering recommendation approach, the trust-based recommendation approach is the emerging one. The reason is that most of online communities allow users to express their trust on other users. Based on the analysis of trust relationships, the trust-based recommendation approach finds out and consults the opinions of more reliable users and therefore makes better recommendations. Existing trust-based recommendation techniques consider all trust relationships in a given trust network equally important and give them the same trust strength. However, in a real-world setting, trust relationships may be of various strengths. In response, in this study, we propose a mechanism for trust strength estimation on the basis of the machine learning approach and estimate the trust strength for each existing trust relationship in a given trust network. To overcome the sparsity of the trust network, we also develop a modified trust propagation method to expand the original trust network. Finally, we perform a series of experiments to demonstrate the performance of our trust-based recommendation approach based on the trust strength estimation mechanism. Our empirical evaluation results show that our proposed approach outperforms our benchmark techniques, i.e., the traditional collaborative filtering approach and the original trust-based one

On radicals of module coalgebras

We introduce the notion of an idempotent radical class of module coalgebras over a bialgebra B. We prove that if R is an idempotent radical class of B-module coalgebras, then every B-module coalgebra contains a unique maximal B-submodule coalgebra in R. Moreover, a B-module coalgebra C is a member of R if, and only if, D B is in R for every simple subcoalgebra D of C. The collection of B-cocleft coalgebras and the collection of H-projective module coalgebras over a Hopf algebra H are idempotent radical classes. As applications, we use these idempotent radical classes to give another proofs for a projectivity theorem and a normal basis theorem of Schneider without assuming a bijective antipode. © 2007 Elsevier Ltd. All rights reserved

Cellular Automaton for Simulation of Oxide Layer Growth Influenced by Chromium Concentration of Structure Material

Chromium, an important alloying element, has been added in ferrous and nickel based alloy such as stainless steels and Inconel alloy to improve the corrosion resistance. High corrosion resistance of structural materials in extremely high working temperature is one crucial R&D objective of Gen IV nuclear power plants which propose to raise the thermal efficiency via high working temperature. A cellular automaton (CA) model based on the stochastic approach was proposed to simulate the process of oxidation and corrosion of structural material in flowing fluid. The relation of chromium concentration against oxide layer thickness during a specific period was found. The material containing a specific amount of chromium content shows the thinnest oxide layer on its surface, which shows the strongest ability of corrosion resistance The result of simulation is close to that of experiments, which demonstrates that the CA model will have potential to achieve the goal of this kind of study. Moreover, it not only brings the benefit to save considerably experimental time and resources but also helps researchers to find out the optimized chromium content for the best corrosion resistance