結果短語 的英文怎麼說
中文拼音 [jiēguǒduǎnyǔ]
結果短語
英文
resultative phrase-
Upon this foundation, a corpus - based algorithm was designed and implemented to acquire and filter binary semantic pattern rules automatically. in the algorithm, a data mining method for cross - level association rules is adopted, which is guided by metarule, to find the semantic laws of word combinations in chinese phrase corpus. then statistic results are used to filter the findings
在此基礎上，本文設計並實現了基於語料庫的二元語義模式規則自動挖掘和優選演算法，該演算法先採用數據挖掘中元規則制導的交叉層關聯規則挖掘方法，自動發現漢語短語熟語料庫中詞語兩兩組合的語義規律，再根據統計結果自動優選后轉換生成候選二元語義模式規則集。The results could be useful for fire alarm system design, which can decrease the visual load, help firefighters ' detection more efficiently, and reduce the casualty
實驗結果為設計者在消防界面中使用語音信號提供了依據，有助於緩解視覺通道壓力，提高信息獲取的速度和準確性，從而縮短火情偵察的時間與范圍，降低火災傷亡。Last, semantic analysis of prepositional phrases is applied to requirement analysis system for mechanical transmission. by system testing, it turns up trumps
最後，將介詞短語的語義分析應用於機械傳動需求分析系統，通過測試，結果比較令人滿意。Semantic analysis of prepositional phrase in nlu ( natural language understanding ) is applied to product design by understanding and analysis of the user requirements in natural language style, which are conversed into the requirement of conceptual design, to support the future design
本文將自然語言理解中的介詞短語和結構的語義分析應用於產品設計中，通過對以自然語言形式表達的用戶需求進行理解和分析，並將分析結果轉化成概念設計要求，為后續設計提供支持。In this paper, a new method of phrase alignment is proposed, where translation head - phrase is obtained according to dictionary - based word alignment which is very reliable, and statistical translation boundary is determined based on the translation extending reliability
提出了一種新的短語對齊方法，使用可信度較高的詞典對齊結果來抽取源語言短語的譯文中心語塊，依據譯文擴展可信度來確定源語言短語的譯文統計邊界。According to the statistical characteristic of noun phrases, we used an iterative re - evaluation algorithm for high - frequency noun phrases, and our metdhod for low - frequence noun phrases is similar to the algorithm for low - frequence content word. this method can take into account the alignment information on the whole, and acquire the result with high coverage rate
名詞短語的對應。本文根據名詞短語的統計特徵，對高頻名詞短語採用迭代重估演算法；對低頻短語，則採用類似於低頻實詞的對應方法。這樣就能夠從整體上把握對應信息，並使結果具有很高的覆蓋率。Dynamic mapping algorithm is also illustrated in details. through the computer simulation to some real short - time voice signal samples using matlab language. the result shows that the recognition efficiency using cepstrum coefficients mapping is better than what made by lpc mapping
實驗結果表明，與採用lpc特徵相比，採用lpc倒譜特徵和動態匹配演算法進行短時語音識別，會有較高的識別率；對不同語音信號有特徵空間離散度大、易於確定判別門限的特點。分享友人