semantic categories 中文意思是什麼
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We shall often find correlation between grammatical and semantic categories.
我們往往會發現語法范疇和語義范疇之間的相互聯系。 -
The ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology, and by means of semantic knowledge. the ontology can improve the effects of document similarity measure and feedback of information retrieval systems
該本體面向特定領域，將關鍵詞以不同權值對應于各分類類目，通過其語義知識來改進文本相似性測度以及信息檢索系統的效果。 -
A method that combines category - based and keyword - based concepts for a better information retrieval system is introduced. to improve document clustering, a document similarity measure based on cosine vector and keywords frequency in documents is proposed, but also with an input ontology. the ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology, and by means of semantic knowledge, the ontology can improve the effects of document similarity measure and feedback of information retrieval systems. two approaches to evaluating the performance of this similarity measure and the comparison with standard cosine vector similarity measure are also described
介紹了一種綜合各層級分類類目和對應關鍵詞來構造概念體系並用於改進信息檢索系統效果的方法.為了改進文本聚類的效果，提出了將領域知識本體和文本關鍵詞詞頻相結合的基於餘弦向量的文本相似性測度方法.該本體面向特定領域，將關鍵詞以不同權值對應于各分類類目，通過其語義知識來改進文本相似性測度以及信息檢索系統的效果.進一步給出了對基於本體的相似性測度方法進行效果評價的2種策略以及該方法與經典餘弦向量測度方法的比較結果 -
In order to solve the problem that current search engines provide query - oriented searches rather than user - oriented ones, and that this improper orientation leads to the search engines ' inability to meet the personalized requirements of users, a novel method based on probabilistic latent semantic analysis ( plsa ) is proposed to convert query - oriented web search to user - oriented web search. first, a user profile represented as a user ' s topics of interest vector is created by analyzing the user ' s click through data based on plsa, then the user ' s queries are mapped into categories based on the user ' s preferences, and finally the result list is re - ranked according to the user ' s interests based on the new proposed method named user - oriented pagerank ( uopr ). experiments on real life datasets show that the user - oriented search system that adopts plsa takes considerable consideration of user preferences and better satisfies a user ' s personalized information needs
針對當前的搜索引擎提供面向查詢、而非面向用戶的服務，從而導致搜索引擎無法滿足用戶個性化的需求這一問題，提出了一種基於plsa的新方法，將面向查詢詞的搜索轉變成面向用戶的搜索.首先，通過分析用戶查詢歷史和瀏覽記錄建立代表用戶模型的用戶興趣向量，在用戶發出查詢時用戶的查詢詞根據用戶興趣向量被映射到興趣分類上，最終根據面向用戶排序演算法將返回結果列表重新排序.實驗表明該面向用戶搜索系統能夠充分考慮用戶的偏好，從而更好地滿足不同用戶的信息需求 -
And semantic typicality involves the interdependency of all the other members except the prototypical member in the category, which is the specific cognition of the meanings in all the sub - categories
范疇原型性表現為能最大限度地抽象概括某一范疇的語義特徵和屬性，是人們對范疇的抽象認知；語義典型性表現為除某一范疇典型成員之外其他各成員之間的相互關系，是人們對各種范疇意義的具體認知。 -
We explored the specific machine learning technique, i. e. bayesian technique in this paper, in the hope of automatically creating such kind of metadata from training data. we assigned wsdl documents to different categories using bayesian latent semantic model. with the frame of blsm, our system classified wsdl documents only by a few of latent class variables and no labeled data
本論文中基於貝葉斯技術的web服務分類演算法的主要思想是通過引入貝葉斯潛在語義模型，首先將含有潛在類別主題變量的wsdl文檔分配到相應的類主題中；接著利用樸素貝葉斯模型，結合前一階段的知識，完成對未含類主題變量的文檔作標注。 -
Li this part, the thesis first profiles semantic features of each document by employing chinese information processing technology in order to change documents into the form which can be operated with the help of mathematical methods. second, the thesis profiles each user ' s information needs by three ways : 1 ) accepting the information provided by the user himself ; 2 ) watching the user ' s retrieval action ; and 3 ) analyzing web server log. in this module, users are also classified into different categories according to their information needs
在用戶建模中，系統從三方面獲取用戶信息需求特徵，第一，用戶主動地向系統提供需求信息；第二，系統檢測用戶檢索行為，從用戶檢索詞分析其需求；第三，系統通過分析web訪問日誌，得到用戶的興趣所在及興趣的變化狀況，並進一步利用對用戶訪問文檔內容的分析來追蹤其興趣變化，將用戶興趣同樣表示為興趣特徵向量，聚類相似用戶。
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