The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based...The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient.展开更多
The topic of this article is one-sided hypothesis testing for disparity, i.e., the mean of one group is larger than that of another when there is uncertainty as to which group a datum is drawn. For each datum, the unc...The topic of this article is one-sided hypothesis testing for disparity, i.e., the mean of one group is larger than that of another when there is uncertainty as to which group a datum is drawn. For each datum, the uncertainty is captured with a given discrete probability distribution over the groups. Such situations arise, for example, in the use of Bayesian imputation methods to assess race and ethnicity disparities with certain insurance, health, and financial data. A widely used method to implement this assessment is the Bayesian Improved Surname Geocoding (BISG) method which assigns a discrete probability over six race/ethnicity groups to an individual given the individual’s surname and address location. Using a Bayesian framework and Markov Chain Monte Carlo sampling from the joint posterior distribution of the group means, the probability of a disparity hypothesis is estimated. Four methods are developed and compared with an illustrative data set. Three of these methods are implemented in an R-code and one method in WinBUGS. These methods are programed for any number of groups between two and six inclusive. All the codes are provided in the appendices.展开更多
In this study, we adopt an improved Bayesian approach based on free-knot B-spline bases to study the spatial and temporal distribution of the b-value. Synthetic tests show that the improved Bayesian approach has a sup...In this study, we adopt an improved Bayesian approach based on free-knot B-spline bases to study the spatial and temporal distribution of the b-value. Synthetic tests show that the improved Bayesian approach has a superior performance compared to the Bayesian approach as well as the widely used maximum likelihood estimation （MLE） method in fitting the real variation of b-values. We then apply the improved Bayesian approach to North China and find that the b-value has a clear relevance to seismicity. Temporal changes of b-values are also investigated in two specific areas of North China. We interpret sharp decreases in the b-values as useful messages in earthquake hazard analysis.展开更多
文摘The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient.
文摘The topic of this article is one-sided hypothesis testing for disparity, i.e., the mean of one group is larger than that of another when there is uncertainty as to which group a datum is drawn. For each datum, the uncertainty is captured with a given discrete probability distribution over the groups. Such situations arise, for example, in the use of Bayesian imputation methods to assess race and ethnicity disparities with certain insurance, health, and financial data. A widely used method to implement this assessment is the Bayesian Improved Surname Geocoding (BISG) method which assigns a discrete probability over six race/ethnicity groups to an individual given the individual’s surname and address location. Using a Bayesian framework and Markov Chain Monte Carlo sampling from the joint posterior distribution of the group means, the probability of a disparity hypothesis is estimated. Four methods are developed and compared with an illustrative data set. Three of these methods are implemented in an R-code and one method in WinBUGS. These methods are programed for any number of groups between two and six inclusive. All the codes are provided in the appendices.
基金jointly funded by the National Natural Science Foundation of China (Grant No.41274052)the Seismological Research Project of China (Grant No.201208009)financially supported by Peking University President’s Research Funding for undergraduate students (2012–2013)
文摘In this study, we adopt an improved Bayesian approach based on free-knot B-spline bases to study the spatial and temporal distribution of the b-value. Synthetic tests show that the improved Bayesian approach has a superior performance compared to the Bayesian approach as well as the widely used maximum likelihood estimation （MLE） method in fitting the real variation of b-values. We then apply the improved Bayesian approach to North China and find that the b-value has a clear relevance to seismicity. Temporal changes of b-values are also investigated in two specific areas of North China. We interpret sharp decreases in the b-values as useful messages in earthquake hazard analysis.
