With the exponential growth of Web data, how to estimate Web page quality effectively and rapidly becomes more and more important for Web information retrieval and knowledge discovery. In this paper, we analyze the di...
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With the exponential growth of Web data, how to estimate Web page quality effectively and rapidly becomes more and more important for Web information retrieval and knowledge discovery. In this paper, we analyze the differences between retrieval target pages and ordinary pages using query-independent features. Using these features, an algorithm called Linear Page Quality Estimation (LPQE) is proposed for Web page quality estimation. Based on the experiments on. GOV corpus and SOGOU corpus involving 26 million pages, about 95% pages can be reduced with more than 90% retrieval target pages retained using LPQE algorithm. Experimental results based on TREC datasets also show that the retrieval performance on collections selected by LPQE can be close to or even better than that on the whole collection.
Multi robot cooperation in etching tools is a complex application since dynamic state changes of all the cooperative robots should be considered in making control decisions. So it is difficult for traditional agent-ba...
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Multi robot cooperation in etching tools is a complex application since dynamic state changes of all the cooperative robots should be considered in making control decisions. So it is difficult for traditional agent-based method (such as belief decision intention (BDI) method) to schedule cooperative etching robots. A dynamic intelligent planning method is required to improve the quality of the decision making process. According to the etching cooperative robot system requirements, this paper proposes a dynamic and intelligent planning method on the base of hybrid BDI agent architecture, which is with evolving artificial neural network (NN) in building the intelligence especially in planning process. As the input of the NN, the working states of every robot can be got easily. And the control decisions for every cooperative robot can be easily made by itself with the evolving neural network. It has been demonstrated effective in actual applications.
An iterative algorithm is presented for the frequency recovery of the band-limited seismic data based on the sparse spike train deconvolution (SSTD) method using the minimum entropy criterion. In this method, we explo...
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In this paper, a dynamically constructive method is proposed for proving the universal approximation for single input/single output (SISO) Takagi-Sugeno (T-S) fuzzy systems, which is superior to the existing construct...
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Performance evaluation is an important issue in Web search engine researches. Traditional evaluation methods rely on much human efforts and are therefore quite time-consuming. With click-through data analysis, we prop...
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ISBN:
(纸本)1595936548
Performance evaluation is an important issue in Web search engine researches. Traditional evaluation methods rely on much human efforts and are therefore quite time-consuming. With click-through data analysis, we proposed an automatic search engine performance evaluation method. This method generates navigational type query topics and answers automatically based on search users. querying and clicking behavior. Experimental results based on a commercial Chinese search engine's user logs show that the automatically method gets a similar evaluation result with traditional assessor-based ones.
A new reconfigurable multi-BMA VLSI architecture was proposed to select different levels of trade-off between video quality, computing complexity and power for power aware applications. The architecture can reuse the ...
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Estimation of distribution algorithms (EDAs) are a class of novel stochastic optimization algorithms, which have recently become a hot topic in field of evolutionary computation. EDAs acquire solutions by statisticall...
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Estimation of distribution algorithms (EDAs) are a class of novel stochastic optimization algorithms, which have recently become a hot topic in field of evolutionary computation. EDAs acquire solutions by statistically learning and sampling the probability distribution of the best individuals of the population at each iteration of the algorithm. EDAs have introduced a new paradigm of evolutionary computation without using conventional evolutionary operators such as crossover and mutation. In such a way, the relationships between the variables involved in the problem domain are explicitly and effectively exploited. According to the complexity of probability models for learning the interdependencies between the variables from the selected individuals, this paper gives a review of EDAs in the order of interactions: dependency-free, bivariate dependencies, and multivariate dependencies, aiming to bring the reader into this novel filed of optimization technology. In addition, the future research directions are discussed.
This paper describes a new technique based on sensor networks for detecting mine methane. By contrast to the traditional methane detection, it has advantages of avoiding unnecessary missed alarm, which might lead to a...
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Aiming at the problem of blind source separation of the communication signals, we propose a step size optimization equivariant adaptive source separation via independence (SO-EASI) algorithm basing on the EASI block b...
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By exploiting the symmetry of bidirectional wavelength-connections in WDM networks, we propose an NxN bidirectional OXC using one N/2xN/2 reversible optical switch to reduce the complexity of the OXCs. The feasibility...
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ISBN:
(纸本)9783800730421
By exploiting the symmetry of bidirectional wavelength-connections in WDM networks, we propose an NxN bidirectional OXC using one N/2xN/2 reversible optical switch to reduce the complexity of the OXCs. The feasibility is demonstrated at 10 Gb/s.
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