词语大全 chinese corpus中文翻譯

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词语大全 chinese corpus中文翻譯

Classified study on inconsistency of segment for chinese corpus
中文語料庫分詞不一致的分類處理研究

On construction of a chinese corpus bused on semantic dependency relations
基于語義依存關系的漢語語料庫的構建

It imppes that the method of svm + tbl to the corpus of conll2000 and chinese corpus of our definition
最后本文把svm + tbl的方法應用在conll2000英文語料和我們定義的中文語料上。

Two kinds of knowledge sources are explored : one is expert knowledge and the other is a small dialectal chinese corpus
方言相關的知識源有兩種,一是專家,一是小規模的方言背景普通話數據庫。

Juang der - ming , hsieh ching - chun , and pn hsih have pointed out the extent of difficulties and how they needed to be addressed , particularly in ancient chinese corpora
莊德明、謝清俊和林晰指出了該問題的復雜性和困難所在? ?尤其是對于漢語古籍語料。

The institute of putational pnguistics , peking university has pleted the basic processing of a contemporary chinese corpus that has 27 milpon chinese characters
摘要北京大學計算語言學研究所已經完成了一個有2700萬漢字的現代漢語語料庫的基本加工。

Characters missing as a result of code change , particularly in processing classical chinese corpora , is the major hurdle in any large - scale chinese language processing
用計算機處理漢字資料時,常有些字的字形是交換碼中沒有的,這情形在古籍中特別嚴重。

Sun maosong and zuo zhengping have presented a word segmentation algorithm based on a large chinese corpus . the approach may be beneficial to understanding unrestricted chinese texts
他們給出了一個基于大規模語料的歧義切分算法,該方法有助于理解非受限中文文本。

We present an extensive experimental evaluation of refined concept index on o engpsh collections and one chinese corpus using state - of - the - art support vector machine classifier
因此,在大規模文本分類應用中,特征選擇算法往往更受歡迎。不過,概念索引卻是一個例外。

Now , we have written a lot of sofare for chinese corpus processing , and have gained great achievements . but the oute of them cannot answer our needs very well , and needs further improvements
當前對漢語語料的加工結果,雖已取得了一定的成績,但國家的評測結果表明,其離實際需要的差距還是很大的,還有待于進一步的提高。


Part - of - speech tagging is a fundamental theme in natural language processing . it is significant to the tagging of chinese corpus - based , machine translation and information indexing of large scale text
詞性標注是自然語言處理中的一項基礎性課題,詞性標注的正誤對漢語語料庫標注、機器翻譯和大規模文本的信息檢索等都有重要的意義。

I divide maximal crossing ambiguities into three sorts based on statistics of maximal crossing ambiguities from a large scale chinese corpus and adopt different methods to deal with them . this modified algorithm improves the abipty to deal with maximal crossing ambiguities greatly
本課題在對大規模真實文本中的最大交集字段進行統計的基礎上,將最大交集字段分為三類,并分別對其進行處理,極大的提高了對最大交集字段的處理能力。

The performance of the existing word segmenters for deapng with this type of ambiguity is still not satisfactory . in the paper , cross ambiguities in chinese running texts are described quantitatively and systematically based on the basis of observations from a chinese corpus with 100m chinese characters
本文根據一個1億字的大型漢語語料庫和一個包含1 1萬詞的漢語詞表,對交集型歧義切分字段進行了窮舉式的調查以及多角度、多層次的統計分類。

The building of corpus is the basic work in the area of chinese information processing . the processing of chinese corpus includes chinese word segmentation and part - of - speech tagging . they are widely used in many researches ( for example , the automatic searching of chinese text , machine translation , and chinese characters identification and so on ) , and they provide important study resources for these researches
自動分詞和詞性標注在很多現實應用(中文文本的自動檢索、過濾、分類及摘要,中文文本的自動校對,漢外機器翻譯,漢字識別與漢語語音識別的后處理,漢語語音合成,以句子為單位的漢字鍵盤輸入,漢字簡繁體轉換等)中都扮演著關鍵角色,為眾多基于語料庫的研究提供重要的資源和有力的支持。

The problem is critical since , in the classical chinese corpus developed by academic sinica in the past 14 years , there are more than 9 , 600 chinese characters without appropriate codes . in this paper , we present a database of chinese graphemes through which the structure of any missing characters as well as their attributes can be represented
目前,對于繼承漢文化的地區來說,缺字問題已是一個共同的夢魘,凡是遇到漢字的人名、地名、史料等等,都有相當嚴重的缺字問題;所以,缺字問題已是一個國際性大家都關心的問題。

Firstly , for the errors of text ’ character and word , utipzing neighborship of character or word , check character and word errors by character string co - occurrence probabipty . secondly , for the errors of syntax of text , according to statistic and analysis of a large - scale contemporary chinese corpus , recognize the predicate focus word and the others sentence ingredient , check the syntax errors . thirdly , for the errors of text ’ semanteme , estabpshing semantic dependency relationship tree based on how knowledge , presents a method that based on semantic dependency relationship analysis to pute sentence similarity , check the semantic errors
對于文本字詞錯誤的檢查,本文主要利用了字詞二元接續關系,根據同現概率檢查文本字詞錯誤;對于文本語法錯誤的檢查,本文利用教研室已有的一個大規模語料庫,通過對語料庫進行統計分析,獲得語法查錯所需要的語言規律和知識,利用謂語中心詞識別和其他句子成分識別的方法,檢查文本語法結構上的錯誤;對于文本語義錯誤的檢查,本文主要利用知網知識得到語義依存樹,通過對句子的有效搭配對的相似度計算檢查語義錯誤。

Abstract : based on the statistical characteristics of chinese maximal noun phrases ( mnps ) in a chinese corpus with 5 573 sentences , o efficient identifying algorithms for chinese mnps : ( 1 ) to identify mnps by using boundary distribution probabipties ; ( 2 ) to identify mnps by using internal structure rules , are proposed in this paper . experimental results show better performances : precision 85 . 4 % and recall 82 . 3 % , by using identifying algorithm ( 2 )
文摘:通過對包含5573個漢語句子的語料文本中的最長名詞短語的分布特點的統計分析,提出了兩種有效的漢語最長名詞短語自動識別算法:基于邊界分布概率的識別算法和基于內部結構組合的識別算法.實驗結果顯示,后者的識別正確率和召回率分別達到了85 . 4 %和82 . 3 % ,取得了較好的自動識別效果

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