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针对农业垂直搜索中中文分词要求的特殊性,提出-5基于词典和全切分的中文分词算法。该算法首先对经过预处理的网页进行基于词典的机械式切分,对未识别的字串再进行基于贝叶斯(Bayes)方法的全切分概率计算,通过计算字串的最大切分可信度确定最合理的切分,并更新词典。实验从120万张农业中文网页中随机抽取14组生成测试集,测试结果表明,该算法与正向最大匹配算法(FMM)和逆向最大匹配算法(RMM)相比具有更高的召回率,F1测度平均达到88%。 相似文献
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Estimating uncertainty in fish stock assessment and forecasting 总被引:8,自引:0,他引:8
Kenneth Patterson Robin Cook Chris Darby Stratis Gavaris Laurence Kell Peter Lewy Benoît Mesnil ré Punt Victor Restrepo Dankert W. Skagen & Gunnar Stefánsson 《Fish and Fisheries》2001,2(2):125-157
A variety of tools are available to quantify uncertainty in age‐structured fish stock assessments and in management forecasts. These tools are based on particular choices for the underlying population dynamics model, the aspects of the assessment considered uncertain, and the approach for assessing uncertainty (Bayes, frequentist or likelihood). The current state of the art is advancing rapidly as a consequence of the availability of increased computational power, but there remains little consistency in the choices made for assessments and forecasts. This can be explained by several factors including the specifics of the species under consideration, the purpose for which the analysis is conducted and the institutional framework within which the methods are developed and used, including the availability and customary usage of software tools. Little testing of either the methods or their assumptions has yet been done. Thus, it is not possible to argue either that the methods perform well or perform poorly or that any particular conditioning choices are more appropriate in general terms than others. Despite much recent progress, fisheries science has yet to identify a means for identifying appropriate conditioning choices such that the probability distributions which are calculated for management purposes do adequately represent the probabilities of eventual real outcomes. Therefore, we conclude that increased focus should be placed on testing and carefully examining the choices made when conducting these analyses, and that more attention must be given to examining the sensitivity to alternative assumptions and model structures. Provision of advice concerning uncertainty in stock assessments should include consideration of such sensitivities, and should use model‐averaging methods, decision tables or management procedure simulations in cases where advice is strongly sensitive to model assumptions. 相似文献