automatic word segmentation造句
例句與造句
- The chinese automatic word segmentation is an important part in the chinese information processing
漢語自動分詞是中文信息處理中的重要環(huán)節(jié)。 - The present paper analyzes such problems as the validity , effect , precision , tolerance , compulsion and limit of automatic word segmentation
機器分詞時會遇到分詞的正確性、加工精度的可容性、機器分詞的強制性、機器分詞的局限性等問題。 - Nowadays , research on chinese information processing focuses on chinese automatic word segmentation , parsing , but seldom in automatic term extraction
目前，國內(nèi)對中文信息處理的研究主要集中在漢語自動分詞、語法分析上，對術語自動抽取的研究還不是很多。 - Besides these , the model of the chinese automatic words segmentation describedin this dissertation can be used to deal with the words segmentation in the situation of command lines
另外，本文所描述的漢語自動分詞模塊已可以在基于命令行的情況下，進行分詞處理。 - The way to segmentation and the anticipated functional criterion that are suited to this subject are illustrated , at last the concrete design of the chinese automatic words segmentation are described , including the overall design and the design of each model
最后詳細描述了漢語自動分詞模塊的具體設計，包括總體設計以及各模塊設計等，同時給出了一些關鍵性的例程說明和程序設計的關鍵點總結(jié)。 - It's difficult to find automatic word segmentation in a sentence. 用automatic word segmentation造句挺難的
- The application of artificial neural network to solve the problem of chinese automatic word segmentation is presented . the mapping model and its performance are studied . based on a number of experiments , the performance of the model is evaluated
神經(jīng)網(wǎng)絡分詞是今后分詞技術發(fā)展的一個趨勢，本文對分詞神經(jīng)網(wǎng)絡進行了研究，建立了分詞神經(jīng)網(wǎng)絡的實驗系統(tǒng)，利用分詞神經(jīng)網(wǎng)絡進行了歧義字段劃分的實驗。 - The automatic and accurate identification of chinese organization names is very significant to improve the accuracy of automatic word segmentation , and it will establish a good foundation for natural language comprehension , machine translation , information extraction and information retrieval
中文機構名稱的自動識別對提高漢語自動分詞的精確率有著重要的意義，也是自然語言理解、機器翻譯、信息抽取和信息檢索的基礎。 - Refer to chinese automatic word segmentation based on statistics , this paper imports the mechanism of open learning , and uses the method of supervised and unsupervised learning . the word segmentation model includes credibility revising and partial tri - gram information
本文在基于統(tǒng)計的漢語自動分詞的基礎上，引入開放學習機制，通過有監(jiān)督和無監(jiān)督相結(jié)合的學習方法，建立包含可信度修正和部分三元語法信息的多元分詞模型。 - Chinese information processing model is added to the traditional search engine , which can make search engine intelligent and personalized . chinese automatic word segmentation is the first work in chinese information processing . in this paper , a chinese word segmentation system is studied , which fits for intelligence search engine
針對歧義字段的劃分問題，提出了歧義字段劃分的三個原則，在三原則的基礎上給出了“二字續(xù)分法”分詞的方案，該方案能夠快速有效的分解大部分的歧義字段，具有很高的實用價值。 - Chinese automatic word segmentation is the fundamental task of the chinese information processing . it mainly comprises of three difficult questions , including word criterion , disambiguation , unknown word identifying . many researchers have contributed to this field , but in the present days , it still needs pursuing higher precision
漢語自動分詞是中文信息處理領域的基礎課題,而且也是進行其它中文信息處理的前提,它有三個主要難點分別是分詞規(guī)范,歧義字段切分和未登錄詞,國內(nèi)外許多研究人員在這一領域都進行了深入的研究,但就目前現(xiàn)狀來看,分詞的正確率仍然有提升的空間。 - At first system accomplishes chinese language automatic word segmentation and part - of - speech tagging through chinese input approach with word segmentation , then forms corresponding surface semantic network according to the semantic structure grammar , and finally gets corresponding data flow diagram and data dictionary according to the automatic generation algorithms of data flow diagram and data dictionary , the whole completion of the work , can not only provide a description environment of natural language for case , but also develop into the system which takes the question described on the basis of the natural language as the system ' s input
工作的中心是自然語言篇章理解。系統(tǒng)首先通過分詞輸入法實現(xiàn)漢語自動分詞與詞性標注，然后根據(jù)語義結(jié)構文法產(chǎn)生相應的表層語義網(wǎng)絡，最后根據(jù)數(shù)據(jù)流圖、數(shù)據(jù)字典自動生成算法轉(zhuǎn)換為相應的數(shù)據(jù)流圖和數(shù)據(jù)字典。這項工作的徹底完成，不僅可以給case提供一個自然語言的描述環(huán)境，而且可進一步發(fā)展為基于自然語言描述問題作為輸入的系統(tǒng)。 - Through discussing such core technologies in the automatic processing of chinese information as automatic word segmentation , feature selecting and automatic representation of texts , the thesis makes some improvements and perfection on the current methods of automatic word segmentation and text space reduction of chinese texts , therefore improved their efficiencies and effects . with regard to the methods of text classification , the paper introduced two supervisory automatic classification methods of chinese texts based on multi - classification , i . e . fuzzy clustering and boosting , which settled the problem of low percentage of recall . through comparing the results of experiments with the two methods , an automatic classification system of multi - classification texts is constructed based on the boosting method , which received good effects in application and provides a good resolution to the problem of real - time classification of information
通過對漢語信息自動處理中自動分詞、特征提取、文本自動表示等核心技術討論，對目前漢語文本自動分詞和文本降維方法中的不足和缺陷作了改進，提高了分詞和文本分類的效率和效果；在文本自動分類方法上，介紹了兩種有監(jiān)督的基于多類的漢語文本自動分類處理方法? ?模糊聚類方法和boosting方法，解決了實踐中文本分類查全率不高的問題；通過對兩種方法的實驗比較結(jié)果，構建了基于boosting方法的多類文本自動分類系統(tǒng)，在實際應用中收到了良好的效果，較好的解決了信息的實時分類問題。 - It discusses and analyzes about automatic word segmentation methods for the chinese language emphatically . moreover it gives the application expectation among this system a method of word segmentation based on the reverse directional maximum matching method . it also proposes that the key of the word segmentation still needs an intact and rational word segmentation dictionary
本文首先研究和討論了基于自然語言的語義分析方法，對漢語的自動分詞方法進行了著重討論和分析，并給出了一種基于反向最大匹配法的分詞方法在本系統(tǒng)中的應用展望，提出分詞的關鍵還需要一個完整合理的分詞詞典。 - The ictclas ( chinese accidence analysis system ) developped by institute of computation technology of china academy of science is used to implement chinese automatic word segmentation and tagging . the algorithm of data mining is used to extract meaningful features that represent the main characteristics of the retrieved documents . then , a novel ideal of virtual concept is proposed to organize the extracted features into specific concepts
用中科院計算所的ictclas漢語詞法分析系統(tǒng)實現(xiàn)中文分詞及標引，并用數(shù)據(jù)挖掘算法提取文檔特征詞條，然后利用本文提出的虛擬概念的思想，將所有特征詞條組織成更有意義的概念，最后，根據(jù)概念間的繼承關系，建立領域自適應概念層次結(jié)構，實現(xiàn)了本體論的自動構造。