query similarity 中文意思是什麼
query similarity
解釋
查詢相似性- query : n 1 質問；詢問；疑問，懷疑。2 敢問，請問〈在疑問句前單獨使用〉。3 【印刷】（打在原稿或校樣上的）...
- similarity : n. 1. 類似，相像，相似。2. 類似點；類似物，相似物。
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Fractal coding has been proved useful for image compression. it is also proved effective for content - based image retrieval. in the paper, we present a block - constrained fractal coding scheme and a matching strategy for content - based image retrieval. in this coding scheme, an image is partitioned into non - overlap blocks of a size close to that of a query iconic image. fractal codes are generated for each block independently. in the similarity measure of fractal codes, an improved nona - tree decomposition scheme is adopted to avoid matching the fractal codes globally in order to reduce computational complexity. our experimental results show that our coding scheme and the matching strategy we adopted is useful for image retrieval, and is compared favorably with other two methods tested in terms of storage usage and computing time
分形編碼在圖像壓縮方面取得了很好的效果，同時，分形編碼也能夠用於基於內容的圖像檢索.本文提出了一種基於塊限制的分形編碼演算法和匹配策略，並將它們用於圖像檢索.在我們編碼演算法中，圖像會被預先分成互相不重疊的子圖像塊，然後對這些子圖像進行獨立地分形編碼，從而獲得整幅圖像的分形碼.該編碼演算法能夠在很大程度上減少編碼時間.在進行圖像間相似性的匹配時，我們採用改進的基於九叉樹的分配策略，從而避免全局地進行分形碼的匹配，減少了計算量.實驗結果說明，我們的編碼演算法和匹配策略能夠比較有效地應用於基於內容的圖像檢索，在計算時間和存儲時間上都優于實驗中其它兩種方法 -
Document similarity search is to find documents similar to a given query document and return a ranked list of similar documents to users, which is widely used in many text and web systems, such as digital library, search engine, etc. traditional retrieval models, including the okapi s bm25 model and the smart s vector space model with length normalization, could handle this problem to some extent by taking the query document as a long query
文檔相似搜索指從文檔集中檢索與給定查詢文檔相似的文檔。對于給定的查詢文檔，我們期望文檔相似搜索系統能夠返回一個按相似度排序的相似文檔列表。文檔相似搜索技術已經被廣泛應用到電子圖書館，搜索引擎等系統中，例如citeseer . ist科學文獻數字圖書館的相似文獻推薦功能， google的相似網頁查詢功能等。 -
A fuzzy image data model and a concept of fuzzy space are proposed, in which model visual feature, spatial feature and semantic feature are used for super feature in order to utilize advantage of traditional relation database as well as characteristics of image data and fuzzy retrieval. based fuzzy space, a method of similarity measurement of image is presented to support fuzzy features - based image retrieval and satisfy user ' s query requirement for image. in the thesis, a semantic template and the mechanism of dynamic relevant feedback are defined so that it can express user ' s query semantic and improve retrieval precision and useable capability for image retrieval
研究了模糊檢索方法和相關反饋機制在圖象檢索中的應用，提出了一種模糊圖象數據模型和模糊空間的概念，該模型將可視特徵、空間特徵、語義特徵看作超屬性，既充分利用了傳統關系數據庫的優點，同時又考慮了圖象數據以及模糊查詢的特點，文中提出的模糊空間和模糊相似性度量方法能支持基於模糊特徵的圖象查詢，較好地體現用戶圖象查詢的應用需求，文中定義的語義模板和相關反饋機制能在一定程度上表達用戶的查詢語義，提高圖象檢索的準確率和易用性。 -
6 we present the query optimization method. for the clustered time series database, the query sequence is classified to one of the cluster, and the efficiency of querying is improved for the similarity search space is limited in the cluster, . 7 we implement a client / server query system and test the presented methods
根據序列數據庫的聚類結果，將序列數據庫劃分為若干層次的簇結構，通過對查詢序列進行k最鄰近分類，確定查詢序列所屬的簇，然後在相應的簇中執行相似性查詢，實驗結果表』明，基於簇的查詢顯著提高了查詢效率。 -
A concept - based approach is expected to resolve the word sense ambiguities in information retrieval and apply the semantic importance of the concepts, instead of the term frequency, to representing the contents of a document. consequently, a formalized document framework is proposed. the document framework is used to express the meaning of a document with the concepts which are expressed by high semantic importance. the framework consists of two parts : the " domain " information and the " situation background " information of a document. a document - extracting algorithm and a two - stage smoothing method are also proposed. the quantification of the similarity between the query and the document framework depends on the smoothing method. the experiments on the trec6 collection demonstrate the feasibility and effectiveness of the proposed approach in information retrieval tasks. the average recall level precision of the model using the proposed approach is about 10 ? higher than that of traditional ones
為了獲取詞語在文章中的語義權重，解決詞語的同義、多義模糊問題，提升信息檢索的效率，提出了一種基於概念的檢索模型，模型中設計了一種形式化的文本內容表示框架，框架由2部分構成:文章的"領域"以及"情景與背景"信息，並由概念（形式化語義）加以表示.同時，提出了提取該概念框架的方法，給出了用於框架與檢索要求間匹配的兩階段平滑演算法.實驗表明，在trec6提供的小規模語料集下，採用所提出方法的信息檢索模型與傳統模型相比，平均召回準確率提升了約10 ? ，效果顯著，充分說明了基於本文描述方法構建的、以概念作為處理中介的信息檢索系統的有效性和可行性 -
Key issues in cbir include extracting features from raw images, matching query and stored images in a way that reflects human similarity judgment
本論文主要針對如何描述圖象內容，準確、自動地提取特徵，以及精確地對圖象內容進行相似性度量。 -
To be exact, if we combine the rough set theory with fuzzy set theory, optimize the users " queries of synonym and homoionym and then return the query results in the descending of similarity of the documents and queries, the users can get the most relevant query results as long as they define their queries according to their interests and describe their interest weight of every keyword in their queries in details
用戶可以先根據自己在某個時刻的興趣愛好自定義查詢，詳細刻畫查詢中各關鍵詞的興趣度，然後系統採用粗糙集和模糊集理論相結合的方法，對用戶查詢進行同義詞、近義詞的優化和回歸，再進行查詢匹配，將查詢結果按其與用戶查詢相似度高低順序返回，使用戶獲得與其興趣最貼近的查詢結果。 -
This paper discusses the existent typical ranking technologies of term frequency count and hyperlink analysis, in virtue of vector space model, the author proposes a new ranking technique, document similarity ranking, with a basis on similarity of concept - semantic query term
對現存典型的詞頻統計排序技術和超鏈分析排序技術進行了分析，並藉助向量空間模型，提出了一種基於概念語義的查詢詞-文檔相似度排序方法。 -
Key issues in cbir include extracting features from raw images, matching query and stored images in a way that reflects human similarity judgement
圖像的內容包括圖像的顏色特徵、形狀特徵、紋理特徵、語義特徵等。 -
So this paper based on fisher discriminant function estimating images similarity, and determine similarity queue of all images in database and query image
因此本文依fisher判別函數來判定圖像相似度，決定數據庫中所有圖像與查詢圖像的相似隊列。 -
Clustering is one of the most important areas in data mining clustering finds the similarity among the data and use it to optimal the query of the large scale databases and find the hidden useful information and knowledge
聚類分析是數據挖掘中的一個重要研究領域，它從數據庫中尋找數據間的相似性，從而優化大規模數據庫的查詢和發現數據中隱含的有用信息或知識。 -
Relevant feedback is also applied in the system, it enable to catch the users ’ query intention by adjusting its similarity criterion automatically ; also, it pass the annotations for the relevant images, update weights between key words and images and fill the semantic networks
通過相關反饋技術理解用戶的意圖，自動調整相似度測量準則以符合用戶的需求;另外，給相關圖像傳遞語義標注，更新相關性強度，充實語義網路。 -
Time series is a kind of important data existing in a lot of fields, such as stock, weather, etc. with time moving, this data of time series will explode increasing. so it is important and challenging subject to research how discovery valuable knowledge in large - scale time series database, and how to search based similarity while user give a graphic query pattern
因此，對這些海量的時序數據如何進行有效的知識發現，挖掘其內在的各種變化模式：對于用戶給定具有各種抽象含義的變化模式，如何在海量時間序列庫中進行相似性的檢索等應用分析，這是一個挑戰性的、具有重要意義的理論和實際應用課題。 -
In order to improve the efficiency, we use the sampling points of the sequences to compute the distance of two sequences. the distance of sampling points is used to filter the sequence of the database, so the similarity searching space is reduced and the efficiency of the query is improved
在保持序列變化模式的前提下，使用抽樣點來計算序列之間的dtw距離，並依據抽樣比率和查詢參數選擇過濾距離對序列數據庫進行過濾，實驗結果表明，抽樣過濾的方法明顯提高了查詢效率。 -
In this approach, the candidate networks from trained keyword queries or executed user queries are classified and stored in the databases, and top - k results from the cns are learned for constructing cn language models cnlms. the cnlms are used to compute the similarity scores between a new user query and the cns from the query. the cns with relatively large similarity score, which are the most promising ones to produce top - k results, will be selected and performed
基於模式圖的在線系統執行機制是，用戶提交關鍵詞查詢后，系統利用數據庫全文檢索引擎為每個具有文本屬性的關系生成包含關鍵詞的元組集，這些元組集與數據庫模式圖相結合，形成元組集圖，然後對元組集圖做寬度優先搜索，生成候選網路candidate network 。
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