semantic matrix 中文意思是什麼
semantic matrix
解釋
語義矩陣-
To solve the problem, a kind of multi - ontology analysis framework consisted of orthogonal matrix made up of multi - dimensional ontology model and temporal model is re - searched ; and then multi - dimension knowledge warehouse based on xml topic maps is constructed, which is developed to implement the accurate and efficient storing and retrieving for knowledge of semantic level
針對這個問題，研究了通過多維本體模型和時域模型的正交矩陣構建的多本體分析框架，並以此為基礎，構建了基於xml主題地圖技術的多維知識倉庫，實現了高效準確的語義級知識的存儲和檢索。 -
It process documents not only based on latent semantic analysis, but also based on text multilevel dependency structure. the method first analysis the latent semantic structure of texts, make single value decomposition on text - matrix, reconstruct the semantic matrix ; then a method based on text multilevel dependency structure is adopted, deeply analysis the content of the semantic matrix, abstract the important sentences to generate abstraction and make up the shortage of latent semantic analysis on structure and syntax
首先通過對文本進行潛在語義分析，對文本矩陣進行相應的奇異值分解，重構語義矩陣;然後採用基於篇章多級依存結構的文摘分析方法，對重構的語義矩陣表示的文本內容進行深入的分析，抽取重要的句子生成文摘，這樣就彌補了潛在語義分析在詞法和句法分析上的不足;同時過濾和去除了語義噪音，縮小了問題的規模。 -
The experimental system extract the low - level features of images such as hsv histogram, the texture got from coexistence matrix, color correlogram, and according to the characteristic of our image database, design the evaluation function such as the average rank ratio to evaluate and compare the performance of different integration of different features including semantic, and validate the active effect of feedback using experiment results
該原型系統提取了hsv直方圖、共生矩陣紋理、顏色相關圖等底層特徵，同時根據圖像數據庫的特點，設計了平均位置比值等評價函數對語義特徵與底層特徵的各種結合的檢索性能進行了比較分析，並對反饋效果進行了實驗驗證。 -
Firstly, one image retrieval framework based on “ fuzzy semantic relevant matrix ” ( fsrm ) is proposed, which uses users ’ relevance feedback sufficiently
首先提出了一種基於「模糊語義相關矩陣」的圖像檢索模型，該模型充分利用了用戶的反饋。 -
This paper researches and discusses the theory of latent semantic index, include the theory of single value decompose and word - document matrix. in this paper the author discusses the application of latent semantic index in chinese document clustering based on latent semantic index, researches and discusses vector space model, latent semantic index, electronic dictionary, word - splitting and the algorithm of k - means. this paper presents a improved structure of electronic dictionary and a improved algorithm of word - spliting
本文對潛在語義索引模型進行系統的研究和探討，包括奇異值分解等相關矩陣理論、詞-文檔矩陣等；同時本文研究和探討了潛在語義索引模型在中文文本聚類中的具體應用和實現，包括文本間相似度的度量、詞-文檔矩陣、奇異值分解的具體實現；同時本文對中文文本聚類所涉及的其他一些中文處理技術，包括向量空間模型、電子字典、切詞、 k - means聚類演算法等也進行了研究和探討。 -
In this dissertation, we use a feature matrix and a semantic relevance matrix which is established by long - term learning the log of the feedback offered by users, then optimize the semantic relevance matrix, and finally, combine the lower - feature matrix and semantic relevance matrix to retrieve images. this approach achieves the estimation of the similarity between
對于某些特殊情況，僅僅依靠修改特徵相似度不能起到很明顯的效果，由此本文引入了語義關系矩陣，先通過對反饋日誌的長期學習建立語義關系矩陣，之後再對語義關系矩陣進行優化，實現了同時被標注為負反饋的圖像之間相似度的估計。
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