vector space model 中文意思是什麼

vector space model 解釋
向量空間模型
  • vector : n 1 【數學】向量，矢量，動徑。2 【航空】飛機航線；航向指示。3 【天文學】幅，矢徑。4 【生物學】帶...
  • space : n 1 空間；太空。2 空隙，空地；場地；（火車輪船飛機中的）座位；餘地；篇幅。3 空白；間隔；距離。4 ...
  • model : n 1 模型，雛型；原型；設計圖；模範；（畫家、雕刻家的）模特兒；樣板。2 典型，模範。3 （女服裝店僱...
  1. Experiments are performed and results show : 1 the popular retrieval models the okapi s bm25 model and the smart s vector space model with length normalization do not perform well for document similarity search ; 2 the proposed model based on texttiling is effective and outperforms other models, including the cosine measure ; 3 the methods for the three components in the proposed model are validated to be appropriately employed

    我們通過實驗驗證了以下三點： 1 trec中的常用信息檢索模型不能很好地解決文檔相似搜索2我們提出的基於texttiling技術的模型是有效的，性能優于其他模型3我們提出的模型中所採用的方法是有效的，包括利用texttiling技術進行文本子主題分割，利用餘弦公式來計算文本塊之間的相似度，以及利用最優匹配方法來求解文檔之間的總體相似度。
  2. 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。
  3. Patent categorization based on kernel vector space model

    基於核向量空間模型的專利分類
  4. Vector space model based on html document structure

    基於向量空間模型的文檔聚類演算法研究
  5. A document searching system with vector space model

    基於向量空間模型的貝葉斯文本分類方法
  6. Design of information retrieval system based on vector space model

    基於合意空間的模糊向量空間
  7. Research for spam filtering based on the vector space model

    基於向量空間的垃圾郵件過濾方法研究
  8. A bayes text classification method based on vector space model

    基於向量空間模型的并行信息檢索演算法
  9. Through the experiment, we test its feasibility. 3 、 to solve the insufficiency of the svm method, the thesis proposes another algorithm based on similarity computing for verb subcategorization acquisition, and use two different sentences similarity getting algorithms to the acquisition : vector space model and the algorithm for sentence structure similarity getting that based on word class cluster

    3 、針對支持向量機方法在自動獲取性能方面的不足，探索提出了基於相似度計算的動詞次范疇獲取演算法，並分別使用了兩種不同的句子相似度獲取演算法:向量空間模型和基於詞類串句子結構相似度獲取演算法，用於動詞次范疇類獲取。
  10. There are two kinds of retrieval model, full text retrieval and content retrieval, and the vector space model ( vcm ) of the latter is a widely - used method with better effect. the best excellence of vcm is the predominance of knowledge presentation, which expresses documents with vectors in vector space and changes the comparability issue to the distance of vectors, and thus reduces the complexity of documents matching. however. we can not affirm the absolute effect of it, and in this thesis we prove its nonproficiency through experiments

    向量空間模型最大的優點在於知識表示方法上的巨大優勢，用n維空間的向量表示文檔，用向量之間的夾角表示文檔的相似度，從而將文檔信息的匹配問題轉化為向量空間中的矢量匹配問題，將難以計算的文字量化成很容易計算的實數，使問題的復雜性大大減小。但是，並不能夠說目前的向量空間模型是最理想的，本文通過實驗證明了vcm表達信息的不精確性。
  11. Meeting the difference of text retrieval and sentence retrieval, a new method using integrating anaphora resolution, improved edit distance and vector space model is proposed in this paper. on factoid question type, the precision of answer sentence retrieval is up to 84. 71 %

    針對文本檢索和句子檢索之間的區別，本文主要採用指代消解預處理，改進的編輯距離與向量空間模型相結合的方法，對factoid問題的答案句檢索效果顯著，準確率為84 . 71 % 。
  12. The feature vector, usedin the vector space model for classification, consists of variousfactors, including the semantic distance from the sentence to the topicand the distance from the sentence to the previous relevant contextoccurring before it

    我們分類採用的特徵向量包含多種因素，其中包括當前句子到話題的語義距離以及當前句子到有效上文句子的距離。
  13. Then it presents the design of information push service based on agent by using artificial intelligence technique. a brief introduction of each function module in this system and their internal transaction sequence are followed. the detail design and implement of key parts in each module is also given, which includes setting up user interest model with vector space model, searching information by using word segmenting and searching engine, filtering information using sorting algorithm, ordering information using pagerank algorithm

    本文首先分析了傳統的信息「拉取」方式存在的主要問題以及推送技術的產生;然後結合人工智慧領域的agent技術，提出了基於agent的信息推送服務的總體設計，並簡要闡述了各功能模塊的內部處理流程和思想;接著給出了各模塊的詳細設計與實現，主要包括:利用向量空間模型（ vectorspacemodel ）建立用戶興趣模型，通過分詞並與搜索引擎協作實現信息檢索，採用分類演算法對已檢索的信息進行過濾，用pagerank演算法對信息排序。
  14. After analyzing the principle of keywords and concept retrieval, a new vector space model named sc - vsm based on the semantic concept retrieval was proposed

    摘要對關鍵詞和概念檢索的原理進行分析后，提出了一種基於語義概念檢索的向量空間模型以及該模型與關鍵詞檢索結合的檢索方法。
  15. According to such an idea, we propose a new retrieval method that combines xpath and vector space model, named as the vector retrieval model based on xpath. secondly, we make full use of the hierarchical architecture of xml data, and analyze the structure of every document to construct a structure thesaurus, which is designed to navigate the user query and to eliminate the structural conflict

    根據這一思想，作者提出了將xpath語言與傳統的向量空間模型相結合，實現基於簡單xpath路徑的向量檢索演算法來實現對xml文檔的檢索。充分利用xml文檔分類層次體系結構的特點，對于每篇xml文檔分析其文檔結構，並採用聚類學習演算法形成文檔結構類屬詞典，從而實現xml文檔查詢的導航機制和消除文檔結構的異構性。
  16. Parallel retrieval algorithm of information based on vector space model

    基於協同過濾的在線拍賣商品推薦
  17. First, this thesis has studied classic information retrieval for document from information retrieval theory, description by math, retrieval model and so on, designed and implemented a content retrieval experimental system based on vector space model

    本文首先針對xml文檔的內容信息，從信息檢索原理、數學描述、檢索模型等方面較全面地研究了傳統的文檔信息檢索技術，設計並實現了一個基於向量空間模型的內容檢索試驗系統。
  18. In vector space model of information retrieval, a text is represented as a weighted vector which is composed of terms weighting of the text

    摘要在信息檢索的向量空間模型中，文本被形式化表示為由詞語權重組成的向量。
  19. 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。
  20. 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。
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