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- In order to reach the aim of knowledge discovery in text,this paper discusses the structure,characters,knowledge source,knowledge orga-nization and structural analysis method of Chin... 文章通过对中文文本的基本结构、主要特征、知识来源、知识组织等的探讨,以期达到文本知识发现的目的。
- Data mining,also known as knowledge discovery in databases. 数据采掘,也称数据库中的知识发现。
- Knowledge discovery in text 文本知识发现
- They provide effective approximate methods for knowledge discovery in FISs. 进而，给出了这两类积分的主要应用：区间数特征对象的分类与融合。
- Outlier detection has always been a hot research field in Knowledge Discovery in Databases (KDD). 孤立点检测一直是知识发现（KDD）中一个活跃的领域，如信用卡欺诈，入侵检测等。
- Association rules is a crucial problem in Knowledge Discovery in Databases（KDD）. 摘要 关联规则是数据库中的知识发现（KDD）领域的重要研究课题。
- Data mining, also known as knowledge discovery in database (KDD), is one of the most active fields in database. 数据挖掘又称数据库中的知识发现，是数据库研究最活跃的领域之一。
- KDD (Knowledge discovery in databases) can find out the effective, novel, latent, and apprehensible information. 知识发现(KDD)能够从数据库中识别出有效的、新颖的、潜在有用的、以及最终可理解的信息。
- Knowledge discovery in databases and data mining aim at semiautomatic tools for analysis of large data sets. 数据库中的知识发现即数据挖掘是致力于大型数据分析中的半自动工具的研究。
- Knowledge discovery in databases, also called data mining, aims at discovery of priviously unknown and potentially useful patterns or knowledge. 在数据库中发现知识，又称为数据发掘，其目标是从大型数据集中发现先前未知的潜在有用的模式或知识。
- For resolving this problem, Knowledge discovery in Data (KDD) and Data-mining Technology are presented to find the information resources. 知识发现和数据挖掘技术就是为迎合这种需要而出现的一种用于开发信息资源的新型数据分析技术。
- DM is core technique in Knowledge Discovery in Database (KDD), and it developed from Machine Learning (ML) of Artificial Intelligence (AI). 数据挖掘是从数据库中发现知识的核心技术,它是从人工智能的机器学习中发展起来的。
- Data mining(DM) as well as Knowledge discovery in Database(KDD) is a new and important research field at the present time. 数据挖掘与知识发现是目前一种新的重要的研究领域。
- Knowledge discovery in database(KDD), a new tool and technique for automatic and intelligent database analysis, is a quite active domain for the moment. 数据库知识发现(KDD)研究如何从大量的数据中智能地、自动地提取出有价值的知识和信息，是当前相当活跃的研究领域。
- Data Mining, also called Knowledge Discovery in Database (KDD), is to extract knowledge or models with potential applicative value from large-size database or data warehouse. 数据挖掘，又称数据库中的知识发现，是指从大型数据库或数据仓库中提取具有潜在应用价值的知识或模式。
- As a promising and flourishing frontier of the Information Technology, Data Mining acts as the essential procedure in knowledge discovery in database (KDD). 数据挖掘是知识发现的核心环节，是信息科学技术发展的必然结果。
- Knowledge discovery in databases is the nontrivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in large data set. 数据库中的知识发现是指在大型数据集中识别有效、新奇、潜在有用、且最终可理解模式的非平凡的过程。
- Knowledge Discovery in Databases (KDD) is a very active field among the subjects of the databases technique, the artificial intelligence, etc. Data Mining is an important step of KDD, can discovery knowledge from the databases. 数据库中的知识发现(Knowledge Discovery in Databases，KDD)是当前人工智能、数据库技术等学科的一门十分活跃的研究领域。
- The CSS font properties define the font in text. CSS字体属性可定义文字所使用的字体。
- Knowledge Discovery in Databases (KDD) is an active research domain nowadays, and it is related to a few subjects such as artificial intelligence and database. Classification is an important research field in KDD. 数据库知识发现是(Knowledge Discovery in Databases,简称KDD)是当前涉及人工智能和数据库等学科的一门相当活跃的研究领域,分类是其中的一个重要研究方向。
