semantic tree 中文意思是什麼
semantic tree
解釋
語義樹-
According to the program structure of ansi c, some syntax - tree - nodes are designed in front - end, including function, block, data structure, type, expression, identifier and so on. syntax tree is divided into three levels, namely program level, function level and block level, which are useful for analysis of syntax and semantic in compiler as well as transferring syntax tree into rtl. retargetable compiler mainly includes intermediate representation, machine description and interface technique between compiler and machine description
編譯前端的實現技術包括詞法分析、語法語義分析和中間代碼生成技術等，針對ansic的程序結構，分別設計了函數、塊、數據結構、類型、表達式、標識符等語法樹結點，並將語法樹分成編譯層次、函數聲明和塊三個不同層次，使語法樹具有清晰的層次結構，有利於編譯程序的語法和語義分析，以及從語法樹到rtl中間表示的轉換。 -
Aiming at this problem, the main research issues and achievements in this paper are as follows : bi - directional data transformation between rdb and xml with semantic constraints preserved for most of existing researches on static data transformation between xml and rdb, dtd is taken as the schema description language for xml, and the semantic constraints are often lost during the transformation process. to overcome these disadvantages, the author adopts xml - schema, a standard schema description language proposed by w3c to replace dtd, as the description method owing to its more powerful functions than dtd, and of course with the syntax much more complicated. after analyzing the constraints characteristics in both xml - schema and relational schema, a semantic constraints - preserved algorithm is proposed which can realize the bi - directional schema mapping between rdb and xml through a formalized description of xml based on regular tree and a general expression for relational schema based on direct graph approach
保留語義約束的xml與rdb雙向靜態數據轉換技術現有研究大多採用dtd （ documenttypedefinition ，文檔類型定義）作為xml的模式描述語言，並且在模式映射過程中丟失語義約束信息，本文分析了xml - schema （ xml - schema採用與dtd完全不同的語法，數據描述能力更強同時也更為復雜，已被w3c確定為替代dtd作為xml模式描述語言的標準）及關系模式的語義約束特徵，通過基於正則樹的xml形式化描述方法以及基於有向圖的一般關系模式表示方法的研究，建立保留語義約束的xml - schema與關系模式的雙向模式映射演算法，實現了xml與rdb的雙向數據轉換，較好地解決了xml與rdb在靜態數據轉換層面的數據集成問題，可有效滿足企業大量rdb數據面向xml的發布以及與日俱增的xml數據存入rdb的應用需求。 -
Firstly, for the errors of text ’ character and word, utilizing neighborship of character or word, check character and word errors by character string co - occurrence probability. 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, establishing semantic dependency relationship tree based on hownet knowledge, presents a method that based on semantic dependency relationship analysis to compute 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。 -
First, the question answering system calculates semantic similarity by using distance between words in semantic tree and the height of semantic tree, then this system uses semantic similarity between words and the weight of word to calculate semantic similarity between users ' questions and questions in answer database
首先，利用語義樹中詞語間的距離和語義樹的高度來計算詞語間的語義相似度，然後利用詞語間的語義相似度和詞語的權重進一步計算用戶問題與答案庫中問題間的語義相似度。 -
An abstract syntax tree is built after syntax analysis and traversed three times to do semantic analysis to generate the intermediate code
在語法分析、語義分析及中間代碼生成方面，先經過語法分析建立抽象語法樹，然後對抽象語法樹進行三次遍歷完成語義分析並生成中間代碼。 -
Different from other researches, autoore uses the proposed java semantic model as input data, and gives a tree - liked, hierarchical structured and semantic cluster set. the clustering method is based on a minimum spanning tree that represents the software system. the clustering objective function is designed according to the software modularization metric and cognition psychology theory
抽象是autoore的核心，它首次採用對象系統的語義關系抽取數據為輸入，利用基於mst表示的、聚集目標結合了程序認知心理學理論的軟體聚集方法，得到一個具有豐富語義的、組織為樹狀的、分層的聚集集合。 -
The framework suppose that the image ' s semantic feature can be expressed by using a multi - level attribute tree, and the probability of a certain image having a certain attribute can be estimated by interpolation method using the neighboring image ' s value. here, the neighboring relation refers to the neighboring in the low - level feature space
該框架假定圖像的語義特徵可用多層屬性樹來近似表示，並且圖像擁有某個屬性的概率值可由相鄰的圖像的概率值進行插值估計，框架中的相鄰指圖像在底層特徵空間的相鄰。 -
This paper uses quadri - tuple to describe semantics contained in information. based on this kind of expression, a tree - like semantic inconsistency detection method is proposed in it
在此基礎上，針對模型中語義不一致檢測和語義調解的工作，提出了樹型的語義檢測方法。
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