[PDF] Top 20 Improved Network Based Recommendation Algorithm

... information. Network-based rec- ommendation algorithms for user-object link predictions have achieved significant ...on network-based algorithm tend to ignore users’ explicit ratings ... See full document

... optimization based on chaotic searching is ...proposed algorithm is better than traditional quantum particle swarm optimization in ability of breaking away from the local optimum, converging speed and ... See full document

... optimization algorithm, and blends the mutation of genetic algorithm into the particle swarm, that is to initialize some variables again at a certain ...of algorithm to find the best ... See full document

... error based on indoor received signal strength indication (RSSI), a RBF neural network (RBFNN) localization algorithm is proposed optimized by improved particle swarm optimization ... See full document

... criterion based on the estimation of the signal-to-noise-ratio figure (SNRF) to optimize the number of hidden neurons in the neural networks to avoid overfitting in the function ...techniques based on least ... See full document

... The improved algorithm can ensure high spectrum utilization taking a little time that is spent on the spectrum ...the improved algorithm is higher than that of the traditional parallel ... See full document

... popular, recommendation systems are very widely applied to various sites ...current recommendation system to be ...filter algorithm, we will introduce the relationship of the trust between the items, ... See full document

... of recommendation due to the sparsity ...adaptive recommendation method based on small-world implicit trust ...trust network based on user clustering and implicit trust among ... See full document

... HE recommendation system is an information filtering system that handles the problem of overload information [1] by filtering fragments of information from a large amount of data ...neighbor algorithm, ... See full document

... item recommendation by first developing a model of user ...Bayesian network, clustering, and rule-based ...Bayesian network model formulates a probabilistic model for collaborative filtering ... See full document

... sensor network (WSN) has been paid more and more attention to by the international academic and industrial ...compared. Based on the existing al- gorithms, an improved time synchronization ... See full document

... TVWS network, there is possibility of high interference among SUs that exceeds the de- sired threshold and also harmful interference to pri- mary users ...TVWS network ignore adjacent channel interference, ... See full document

... road network, which should be comparable to the current 1:200,000 map product of swisstopo, ...general network thinning was rated as ...density algorithm (Figure ...road network structures, ... See full document

... of network life ...the network longevity. In our improved LEACH protocol, residual energy is also taken as a parameter during the selection of cluster head which helps in network maximization ... See full document

... e-commerce recommendation system, has played a significant role in practical ...filtering recommendation technology theoretically, aiming at improving the accuracy of personalized ...Clustering ... See full document

... Due to the fact that CR networks are made up of plen- tiful high density distribution of base stations, sensor nodes and users, resource allocation should take fully into account parameters such as free carrier quantity, ... See full document

... users based on their social graphs, which may not be the most appropriate to reflect a user’s preferences on friend selection in real ...friend recommendation system for social networks, which recommends ... See full document

... technique based on the PEGASIS protocol using an improved ant colony algorithm and neural network rather than the greedy algorithm to build the chain is ...networks algorithm to ... See full document

... product recommendation engine has become a key aspect of e-commerce website ...product recommendation engine is important decision you make to help your company improved talk with ...product ... See full document

... evolutionary algorithm based on decomposition (MOEA/D) for this MOP by hybridizing it with the population-based incremental learning techniques, which makes use of the global and historical ... See full document