Within the scope of the course computerscience in Mechanical engineering, a blended learning concept is used in order to teach students of mechanical engineering the basic principles of computerscience. This concept...
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A runtime system for implementation of image processing operations is presented. It is designed for working in a flexible and distributed environment related to the software architecture of a newly developed UAV syste...
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Service discovery protocols are extremely important for developing distributed applications in ad-hoc environments. However to perform Service Discovery in mobile ad-hoc networks requires the design and development of...
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Since we can hardly get semantics from the low-level features of the image, it is much more difficult to analyze the image than textual information on the Web. Traditionally, textual information around the image is us...
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Defining and using ontology to annotate web resources with semantic markups is generally perceived as the primary way to implement the vision of the Semantic Web. The ontology provides a shared and machine understanda...
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We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user inter...
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We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user＇s interests. This expression represents a user＇s specific and general interests as a continuurn. In some sense, specific interests correspond to shortterm interests, while general interests correspond to longterm interests. So this representation more really reflects the users＇ interests. The algorithm can automatically model a us er＇s multiple interest domains, dynamically generate the in terest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.
Many previous works of data mining user queries in Peer-to-Peer systems focused their attention on the distribution of query contents. However, few has been done towards a better understanding of the time series distr...
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Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve...
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ISBN:
(纸本)0769525288
Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under this framework, we use two prevalent evolutionary algorithms: Genetic, Algorithm (GA) and Particle Swarm Optimization (PSO) to find unknown sites in a collection of relatively long intergenic sequences that are suspected of being bound by the same factor. This paper represents binding sites motif to position weight matrix (PWM) and introduces how to code PWM to genome for GA and how to code it to particle for PSO. We apply these two algorithms to 5 different yeast Saccharomyces Cerevisiae transcription factor binding sites and CRP binding sites. The results on Saccharomyces Cerevisiae show that it can find the correct binding sites motifs, and the result on CRP shows that these two algorithms can achieve more accuracy than MEME and Gibbs Sampler.
The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed...
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The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient.
This paper presents technical foundation, roadmap and initial results of the IDIOM project (Information Diffusion across Interactive Online Media). Information spreads rapidly across Web sites, Web logs and online for...
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