詞義消歧 的英文怎麼說

中文拼音 [cíyìxiāoqí]
詞義消歧 英文
word sense disambiguation
  • 詞 : 名詞1 （說話或詩歌、文章、戲劇中的語句） speech; statement; lines of play 2 （一種韻文形式 起於唐...
  • 義 : Ⅰ名詞1 （正義） justice; righteousness 2 （情誼） human ties; relationship 3 （意義） meaning; si...
  • 消 : 動詞1 （消失） disappear; vanish 2 （使消失; 消除） eliminate; dispel; remove 3 （度過; 消遣） pa...
  • 歧 : Ⅰ名詞（岔道; 大路分出的路） fork; branchⅡ形容詞（不相同; 不一致） divergent; different
  1. Hemispheric asymmetry in solving lexical ambiguity in chinese

    漢語同形歧義詞歧義消解的兩半球差異
  2. The process of the disambiguity of homographs in chinese

    漢語同形歧義詞歧義消解的過程
  3. The inhibition mechanism for resolving lexical ambiguity of two - syllabe homophones in chinese

    漢語同音歧義詞歧義消解的過程及其抑制機制
  4. A review of researches on lexical ambiguity resolution

    詞匯歧義消解的研究概況
  5. Word sense disambiguation ( wsd ) is an important research project in computalitonal linguistics and natural language processing ( nlp ), and is also one of hot spot research problems in nlp in recent years

    詞義消歧（ wordsensedisambiguation ， wsd ）是計算語言學和自然語言處理領域一個重要的研究課題，也是近些年來該領域的熱點研究問題之一。
  6. 46 du l, sun y f. a new indexing method based on word proximity for chinese text retrieval. journal of computer science and technology, 2000, 15 : 280 - 286

    詞義消歧以語料庫為主要知識源，根據對已標注語料的利用分為無指導有指導和半指導的方法。
  7. 2. investigating how to model the wsd. the na ? ve bayes model, maximum entropy, support vector machine and decision trees model are examined in chinese wsd

    2 .考察了貝葉斯模型、最大熵模型、支持向量機和決策樹模型等四種數學建模方法在詞義消歧上的應用效果。
  8. Chinese wsd based on context calculation model

    基於語境計算模型的漢語詞義消歧
  9. An introduction of word sense disambiguation based on bayers model

    淺談基於改進貝葉斯模型的詞義消歧方法
  10. 3. introducing the concept of equivalent pseudowords and the method of its construction, and achieving unsupervised wsd method by them

    3 .提出等價偽詞概念和等價偽詞的構造方法，並以此實現無指導的詞義消歧方法。
  11. In brief, the article has done some useful attempts in machine learning and unsupervised wsd methods, and gets some initial findings. with devotion of

    綜上所述，本文在機器學習和無指導的詞義消歧方法上都作了一些有益的嘗試，取得了一些初步成果。
  12. The main emphasis of our research is statistical word sense disambiguation, which can be classified into two categories according different discipline methods : supervised and unsupervised

    本文研究的重點在於統計詞義消歧技術，它根據使用的訓練方法的不同可以分為有指導和無指導的兩大類。
  13. The former includes chinese word segmentation, part - of - speech tagging, pinyin tagging, named entity recognition, new word detection, syntactic parsing, word sense disambiguation, etc

    前者涉及到詞法、句法、語義分析，包括漢語分詞、詞性標注、注音、命名實體識別、新詞發現、句法分析、詞義消歧等。
  14. The experiment introduces that the concept of equivalent pseudowords and unsupervised wsd technology based on equivalent pseudowords provide a new thought and method for exploring the new technology of wsd

    實驗表明等價偽詞的概念以及建立在等價偽詞基礎上的無指導詞義消歧技術為探索詞義消歧的新技術提供了一個新的思路和方法。
  15. Meanwhile it accelerates the search process by cache. ( 3 ) the chinese word segmentation module to support the text segmentation of system, it uses hmm - based disambiguation algorithm to improve the accuracy of the word segmentation. ( 4 ) the search module to response the users ’ search request, it applies an efficient clustering / classification algorithm to optimize the search service quality

    它使用基於hmm模型的歧義消除演算法來提高分詞預處理的切分精度。 （ 4 ）檢索模塊用來響應用戶的查詢請求。它利用簡單靈活的聚類/分類演算法來優化系統的搜索服務。
  16. Word sense disambiguation model

    詞義自動消歧概率模型
  17. Comparing word sense based language model to other language models, the experiments based on the corpus of trec shows that wslm method has a better performance than the traditional td - idf method. if a more powerful word sense disambiguation tool is used, the result could be improved. in the retrieval results re - ranking part, we use a combination method which combines the retrieval results of different system by linear interpolation

    在基於詞義語言模型的信息檢索研究中，介紹了同義詞詞典的詞義表示方法，在實驗中使用trec語料把基於詞義的語言模型並與其他語言模型進行了比較，實驗表明，基於詞義的語言模型方法要好於傳統的td - idf方法，如果有更加精準的詞義消歧工具，實驗結果還會有進一步提高。
  18. We try the unsupervised wsd method based on equivalent pseudowords by the na ? ve bayes model and maximum entropy in paper. it gets 81 % correct rate on the test data of senseval - 3, which is obvious better than supervised method accordingly

    利用得到的兩種較優的機器學習方法:貝葉斯模型及最大熵模型，本文嘗試了基於等價偽詞的無指導詞義消歧方法，在senseval - 3的測試數據上獲得了81 %的正確率，明顯優于相應的有指導方法。
  19. A semantic based disambiguation algorithm was designed and implemented. with the algorithm, word sense disambiguation and structure disambiguation can be done by semantic pattern rules matching during syntax parsing. the experiment result indicates that : ( a ) the presentation of semantic pattern rules can formalize the construction of chinese phrase quite well ; ( b ) the corpus - based algorithm for acquiring and filtering binary semantic pattern rules is effective, and it can reduce the human labor, avoid subjectivity and unilateralism caused by writing rules manually ; ( c ) the semantic based disambiguation algorithm can achieve satisfactory effects

    實驗表明： 1 ）本文設計的語義模式規則能夠較準確地刻畫漢語短語構造的語義規律； 2 ）本文提出的基於語料庫的二元語義模式規則自動挖掘和優選演算法是切實可行的，它大大減少完全由人工從大規模語料庫中總結規則的工作量，避免了純人工編制規則的主觀性和片面性； 3 ）本文提出的語義分析排歧演算法能夠有效消解短語分析中的詞義歧義和結構歧義。
  20. It adopt an algorithm called binary - seek by character in the word rough segmentation. it also designs some efficient strategies to deal with the ambiguities and the unknown words, especially for combinational ambiguity, it designs a new disambiguated algorithm in case - learning method based on the structured similarity of the chinese sentences

    本文採用基於詞典的逐字二分查找方法實現粗切分，並對歧義切分和未登錄詞識別設計了相應的處理策略;特別是針對組合型歧義，本文提出了基於句子結構相似度的事例學習消歧方法。
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