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Web users display their preferences implicitly by a sequence of pages they navigated. Web recommendation systems use methods to extract useful knowledge about user interests from such data. We propose a Bayesian nonparametric approach to the problem of modeling user interests in recommender systems using implicit feedback like user navigations and clicks on items. Our approach is based on the discovery...
In order to formally model and theoretically analyze grid scheduling of super-peer model, we propose a kind of new resource scheduling algorithm allowing a grid user to put forward the task's expected execution deadline, cost limit and the weight parameters between them. Then, we use hierarchical colored and price timed Petri net to model and simulate the dynamic process of grid scheduling, mapping...
Similar to product recommendation used in e-commerce sites and other fields, the recommendation of web service often take advantage of the history invocation information of users and services (denotes as QoS, Quality of service) to predict the unknown QoS value and then recommend web services to the active user with the best QoS. In order to adapt to the complex and changeful prediction occasions...
The successful design of collaborative filtering system for recommending depends hardly on finding the nearest neighbors. In this paper, we provide a new collaborative filtering method based on concept lattices to generate more precise recommendation. Firstly, we analyze the log files and construct a formal context which is then used to build a concept lattice. Based on the concept lattice, we propose...
Based on the analysis of endoscope image, in this paper, a new color quantification method is proposed to extract improved CCV and the V component shape invariant moment achieving image feature base. Inspiring from general information searching, the two-level content-based endoscope image retrieval is represented using the improved CCV and V component shape invariant moment guaranteeing the first...
Firstly, this paper presents ontology modeling based on the task-space model given previously in a collaborative learning environment. Designing and developing a Web-based collaborative learning system in the light of this model, the key problem of resource management can be resolved at individual levels. In this way, some disadvantages, such as non-uniform knowledge description, inefficiency of knowledge...
In this paper, improved CCV is extracted as retrieval feature using a new quantification method which is proposed based on the analysis of endoscope image color distribution in different color spaces. It is proved that with this quantification, the improved CCV displays better retrieval effect.
Content-based medical image retrieval is getting more and more importance in aspect of clinical assistant diagnose. This paper in allusion to gastroscopic images, make use of latent semantic indexing technology to implement image retrieval which based on its semantic information. First extract image's histogram of neighborhood color moments of low-level features, and then use normalizing, term weighting...
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