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- The Method of Web Text Classification of Using Non-labeled Training Sample 无标记训练样本的Web文本分类方法
- Web text classification Web文本分类
- A comparison of event models for Naive Bayes text classification. 如果在监督环境下,即文本的类别已知。
- This text bases on the previous methods of text classification,passing to analyze the Web structure,puts forward a method of using extended anchortext for classifying Web pages. 在以往一些分类方法的基础上,通过分析网页自身的结构,提出了一种利用扩展锚点文本来对网页进行自动分类的方法。
- This paper presents a rough set theory based on the text classification. 文章提出了一种基于粗糙集理论的文本分类方法。
- The KNN is a simple,valid and non-parameter method applied to WEB text categorization. KNN算法是一种简单、有效、非参数的Web文本分类方法。
- Feature selection is one of key factors that influences the development of text classification. 摘要特征选择是影响文本分类技术发展的关键因素之一。
- Make a study of applications of ontology to two domains such as text classification and information retrieval. 对Ontology 的应用在文本分类和信息检索两个领域进行研究。
- Jianlin Feng, Huijun Liu, Yucai Feng: Sentential Association Based Text Classification Systems. 何玉，冯剑琳，王元珍。基于最大关联规则的文本分类。
- Text classification feature selection in text categorization is the first important problem to be solved. 摘要文本分类特征选择是文本自动分类中首先要解决的重要问题。
- This paper construct a Dublin Core metadata for web text data. This kind of metadata can convert web text data which is unstructured data into structurual data. 本为为web数据中的文本数据建立了一种Dublin Core文本元数据表，将web文本这种非结构化数据结构化。
- Experiment results show that, for both text classification and non-text classification, DRC-BK has excellent classification performance. 实验表明,本文提出的DRC-BK 在文本分类领域和非文本分类领域都具有优秀的分类性能。
- Text classification methods based on Key words are not known for their classification precision,this is due to the existence of synonyms and polysemes. 由于同义词和多义词的存在,使得基于特征词的文本分类方法分类精度不高。
- This text classification system got the highest score among runs from 19 groups in the evaluation of TREC 2005 Genomics Track Categorization Task. 该系统在2005年文本检索会议(TREC;Text REtrieval Conference)的基因领域文本分类任务(Genomics Track Categorization Task)的评测中取得第一名.
- Thispaper first studies the text classification algorithms, discusses how to extract featureterms, and implements a new feature extraction algorithm. 本文首先对文本分类算法进行了研究,探讨了文本特征抽取方法,其中综合考虑了频度、分散度和集中度三项指标,设计并实现了一种新的特征抽取算法,使得选出的特征项整体优化。
- The dissertation researches the Web text mining in detail according to the process of Web text mining, constructs a Web text mining model based on extensible Markup Language (XML) and Support vector machine (SVM). 论文依照Web文本挖掘的过程对Web文本挖掘进行了详细的研究,构建了一个基于可扩展标记语言(XML)和支持向量机(SVM)的Web文本挖掘模型。
- To solve this problem, we propose a new text classification model: Latent Semantic Classification (LSC) model by extending LSI model. 针对上述问题,在扩展LSI模型的基础上,我们提出了一种新的文本分类模型:潜在语义分类模型(Latent Semantic Classification:LSC)。
- Text orientation recognition has broad application in some field such as information filtering，automatic abstracting and text classification. 摘要 文本倾向性识别在信息过滤、自动文摘、文本分类等领域有广泛的应用前景。
- The site can be navigated to locate species using text classification or a graphical tool, both linked to the evolutionary tree of life. 网站可以利用文字或是图形方式将读者引导至物种页面，并连结到相关的生命演化树。
- Web mining is to make use of the techniques of data mining to extract interesting,potential,useful pattern and hidden information from Web texts and Web activities. Web挖掘就是利用数据挖掘技术,从Web文档和Web活动中提取感兴趣的、潜在的有用模式和隐藏的信息。
