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proper noun 【語法】專有名詞。

properdin

After that , it discusses the proper nouns recognition algorithms designed for our proper nouns recognition system in detail : dividing all proper nouns into two categories , one category is named stable proper nouns , which contains the proper nouns that will exist in a long term and a wide spread ; and the other category is called unstable proper nouns , proper nouns in this category often derives new proper nouns frequently and can not be formed following particular rules , the mainly proper nouns in this category are chinese names 接著本文詳細討論了專有名詞識別系統所使用的識別算法:首先將專有名詞分成了兩類:一類是穩定的專有名詞,此類名詞具有長時間和較大范圍存在的特點。另一類是容易變化的專有名詞,這類名詞新詞出現速度快,并且沒有明顯的規律可循,這類名詞主要就是中國人名。

This thesis proposes a novely approach to recognize proper nouns and the recognition system is realized based on the approach . the system is tested on several groups of data , and the results show that the performance is satisfactory , and the open test results also show that the system ’ s capability of recognizing proper nouns is of great 文章提出了一個識別專有名詞的方案,并且根據此方案實現了一個識別系統,同時進行了多項數據試驗,對專有名詞的識別研究具有一定的參考價值;開放測試的結果也表明,該系統的專有名詞識別能力也達到了較好的實用水平。

If the term extraction transformation is configured to extract only noun phrases , words that are tagged as nouns , proper nouns , adjectives , and numbers may be combined to make a noun phrase , but the phrase must include at least one word that is tagged as a singular or plural form of a noun or a proper noun 如果將字詞提取轉換配置為僅提取名詞短語,那么標記為名詞、專有名詞、形容詞和數詞的單詞可以組合成名詞短語,但該短語必須包含至少一個標記為單數或復數形式的名詞或者專有名詞的單詞。

Disambiguity and recognition of unknown words are most important points for design of word segmentation systems . in this paper , firstly , we introduce an applied strategy to disambiguity . then we put forward an integrated and fast recognition strategy of proper noun , including chinese person names , chinese place names , translated foreign names and corporation & organization names , in modern chinese word segmentation system , which successfully resolves the conflict among these proper nouns and ordinary words 本文首先闡述了現代漢語通用分詞系統( gpws )中歧義切分技術和專名識別技術,在歧義切分技術中,提出了一種切分規則庫與基于歧義知識庫動態校正相結合的實用歧義處理策略;在專名識別技術中,本文提出了一種專名(包括譯名在內的人名、地名、企業字號、企業名和機構名等)一體化、快速識別方法。

Named entity recognition ( ner ) technologies have become a hot problem of natural language process recently . the definition of named entity by muc ( message understanding conference ) is the proper nouns and the quantifiers that people are interested in . ner can be classified to person - name , location , organization , date , number and so on . ner has been applied on many compute linguistics tasts as a subtask of information extraction , such as machine translation 命名實體識別是目前自然語言處理研究的熱點問題。 muc ( messageunderstandingconferences )對命名實體的定義是:人們感興趣的專有名詞和特定的數量詞,它一般可分為:人名、地名、組織機構名、日期等類型。

Firstly , the issues of recognizing proper nouns are discussed as well as the popular approaches are presented and compared , and according to the analysis , a new approach , namely using rules primarily to recognize proper nouns , is evoked for the purpose . then , after analyzing the main idea and presenting the design , it shows the system design in detail , including defining basis concepts , pre - processing text , collecting proper nouns ’ information , extracting rules and labeling properties . finally , the system realization is divided into two parts and detailed illuminate is presented respectively 本文首先圍繞專有名詞識別問題展開討論,在分析和比較了現有的專有名詞識別方案和常用方法后,明確了課題目標;在此基礎上,提出了一個以規則為主的專有名詞統一識別方法;然后,在提出了課題的設計思想,對課題的設計方法進行了一個整體的概括介紹后,進行了詳細的系統設計說明,主要包括:基本概念的定義、文本預處理、專有名詞特征信息集的建立、規則的提取和屬性標注等五個方面。

Taking the member / academician dispute as a case , this paper discusses , from the concept of cultural communication of translation as well as the angle of cultural cognition tolerance , the translator ' s motive and chinese readers ' cultural cognition tolerance in retranslating english proper nouns 摘要透過“許傳璽院士”風波,從翻譯的文化交流觀和文化認知容忍度的角度出發,探討了英語專有名詞漢語重譯的動機和中國讀者對此的文化認知容忍度的問題。

After dividing proper nouns in two categories , this paper discusses different algorithms for these two categories : for the first category we use proper nouns database to recognize it , and for the second category we use the recognizing method base on native bayesian classification algorithm 然后對這兩類專有名詞設計不同的識別方法:對第一類專有名詞使用的基于專有名詞詞庫的識別算法;對第二類專有名詞使用的基于樸素貝葉斯分類的識別算法。

The authors hold that the concept of cultural communication is worth deeply thinking by translators , and whether the retranslation of english proper nouns concerning titles is “ standard “ or not should be decided according to chinese readers ' cultural cognition tolerance at present 認為翻譯的“文化交流觀”值得翻譯工作者思考;而步及“頭銜”的一些英語專有名詞的重譯是否更“標準” ,這需要聯系當前中國讀者對此的文化認知容忍度來判斷。

The proper nouns usually derives new words frequently , easy to change or disappear , and can not be formed following particular rules , all of these cause the proper nouns hard to be recognized in the sentence and make chinese word segmentation difficult 專有名詞存在新詞出現快,成詞無固定規則,容易變化等特點,給漢語分詞帶來了很大的干擾,使專有名詞的識別成為漢語分詞的一大瓶頸。

In addition to word segmentation and part - of - speech tagging , the processing involves the tagging of proper nouns ( person names , place names , organization names and so on ) , morpheme subcategories and the special usages of verbs and adjectives 加工項目除詞語切分和詞性標注外,還包括專有名詞(人名、地名、團體機構名稱等)標注、語素子類標注以及動詞、形容詞的特殊用法標注。

In addition to word segmentation and part - of - speech tagging , the processing involves the tagging of proper nouns ( person names , place names , organization names arid so on ) , morpheme subcategories and the special usages of verbs and adjectives 加工項目除詞語切分和詞性標注外,還包括專有名詞(人名、地名、團體機構名稱等)標注、語素子類標注以及動詞、形容詞的特殊用法標注。

In this novelty approach , proper nouns “ term information together with rules attained by transformed - based error - driven learning is used to label properties of segmented text , so as to recognize proper nouns 該方法利用從語料庫中自動提取到的專有名詞信息和采用基于轉換的錯誤驅動學習方法獲得的規則,對切分文本進行屬性標注,最終實現專有名詞的識別。

Word segmentation is the foundation of chinese information processing , and its performance is influenced extremely by the recognition of unknown words , especially the recognition of proper nouns 中文信息處理的基礎是分詞。影響分詞準確率的重要因素之一就是未登錄詞的識別,而未登錄詞識別的難點是專有名詞識別。

Translating the content rather than the form is a typical feature of good translation and it ' s very common even in practical translation of proper nouns which requires strict exactness and subtlety 即使在今天對翻譯要求嚴格、細膩的專有名詞的翻譯中“得意忘象”式的翻譯也是好翻譯的一個顯著特征。

According to proper nouns ’ internal structures and their context , this thesis proposes a novely approach to recognize proper nouns , namely using rules primarily to recognize proper nouns 本文針對專有名詞內部結構特點及其上下文詞語環境特點,提出了一個以規則方法為主的專有名詞統一識別方案。

At first , the paper introduces the progress of computer natural language processing , especially the chinese language processing , and the methods used for proper nouns recognition 文章首先介紹了計算機自然語言處理,特別是漢語的計算機處理的現狀以及目前漢語分詞中使用的專有名詞識別方法。

If the term extraction transformation is configured to extract only nouns , only the words that are tagged as singular or plural forms of nouns and proper nouns are extracted 如果將字詞提取轉換配置為僅提取名詞,那么將只提取標記為單數或復數形式的名詞和專有名詞的單詞。

Large - scale test on real corpus show that both of these strategies have got high performance and precision in disambiguity and recognition of proper nouns 從大規模真實語料的測試結果來看,歧義切分處理的精度、專名識別的正確率和召回率均達到了較高的水平。