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semantic knowledge in Chinese

Pronunciation:
How to pronounce "semantic knowledge""semantic knowledge" in a sentence

Translationmobile phoneMobile

  • 語義知識(shí)

Examples

  • You will also have to have the linguistics and some semantic knowledge
    你也將會(huì)必須有語言學(xué)和一些與語意有關(guān)的知識(shí)。
  • First we put forward the general idea about this method and give a brief introduce to its semantic knowledge resource - the hownet dictionary
    本文首先提出了這種方法的總體思路，并對(duì)其語義知識(shí)資源《知網(wǎng)》作了簡要的介紹。
  • In cfm , there exists the semantic knowledge about chinese clause and it includes the semantic modes which are the basic modes used to represent the human ' s experience , and the elementary concepts which are the components of semantic mode
    Cfm中擁有漢語小句級(jí)的語義知識(shí)，它包含了小句的“語義模式”以及組成“語義模式”的“基元概念” 。
  • The ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology , and by means of semantic knowledge . the ontology can improve the effects of document similarity measure and feedback of information retrieval systems
    該本體面向特定領(lǐng)域，將關(guān)鍵詞以不同權(quán)值對(duì)應(yīng)于各分類類目，通過其語義知識(shí)來改進(jìn)文本相似性測(cè)度以及信息檢索系統(tǒng)的效果。
  • A method that combines category - based and keyword - based concepts for a better information retrieval system is introduced . to improve document clustering , a document similarity measure based on cosine vector and keywords frequency in documents is proposed , but also with an input ontology . the ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology , and by means of semantic knowledge , the ontology can improve the effects of document similarity measure and feedback of information retrieval systems . two approaches to evaluating the performance of this similarity measure and the comparison with standard cosine vector similarity measure are also described
    介紹了一種綜合各層級(jí)分類類目和對(duì)應(yīng)關(guān)鍵詞來構(gòu)造概念體系并用于改進(jìn)信息檢索系統(tǒng)效果的方法.為了改進(jìn)文本聚類的效果,提出了將領(lǐng)域知識(shí)本體和文本關(guān)鍵詞詞頻相結(jié)合的基于余弦向量的文本相似性測(cè)度方法.該本體面向特定領(lǐng)域,將關(guān)鍵詞以不同權(quán)值對(duì)應(yīng)于各分類類目,通過其語義知識(shí)來改進(jìn)文本相似性測(cè)度以及信息檢索系統(tǒng)的效果.進(jìn)一步給出了對(duì)基于本體的相似性測(cè)度方法進(jìn)行效果評(píng)價(jià)的2種策略以及該方法與經(jīng)典余弦向量測(cè)度方法的比較結(jié)果
  • In this paper , we elaborate an intelligent search agent working on the internet , introduce the conception of ontology into the agent , make use of ability of ontology to describe semantic knowledge , set up a simple model of information agent using ontology to standardize the user ' s requests , analyze the results returned by the search agent and study the user ' s interests in order to let the information agent to retrieve information for users without requests
    本文對(duì)因特網(wǎng)上的智能搜索agent作了比較深入的研究，將本體引入到智能信息agent中來，利用本體對(duì)語義知識(shí)描述的特長，在某個(gè)領(lǐng)域內(nèi)建立一個(gè)簡單的本體實(shí)例，用來規(guī)范本體的查詢請(qǐng)求、分析處理搜索代理返回的搜索結(jié)果、學(xué)習(xí)用戶的興趣愛好，使其能自主的為用戶查找用戶感興趣的信息。

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