论文标题
一种基于自动新闻检索功能组合的方法
An approach based on Combination of Features for automatic news retrieval
论文作者
论文摘要
如今,根据信息的越来越多,其演示的重要性也在增加。互联网已成为用户及其最喜欢的主题的主要信息来源之一。它还可以访问更多信息。了解此信息对于为用户提供最佳信息资源非常重要。现在,内容提供商需要一种精确,有效的方法来在人类最少的帮助下检索新闻。数据挖掘已导致出现用于检测相关文档和无关文档的新方法。尽管文档之间的概念关系可能可以忽略不计,但向用户提供有用的信息和相关内容很重要。在本文中,介绍了一种基于特征(COF)的新方法用于信息检索操作。除了引入这种新方法外,我们还通过识别文档中最常用的关键字并使用最合适的文档来帮助他们提供丰富的词汇,提出了一个数据集。然后,使用建议的方法,文本分类,评估标准和排名算法的技术,对数据进行了分析和检查。评估结果表明,使用特征方法的组合可以提高对有效排名的质量和影响。
Nowadays, according to the increasingly increasing information, the importance of its presentation is also increasing. The internet has become one of the main sources of information for users and their favorite topics. It also provides access to more information. Understanding this information is very important for providing the best set of information resources for users. Content providers now need a precise and efficient way to retrieve news with the least human help. Data mining has led to the emergence of new methods for detecting related and unrelated documents. Although the conceptual relationship between documents may be negligible, it is important to provide useful information and relevant content to users. In this paper, a new approach based on the Combination of Features (CoF) for information retrieval operations is introduced. Along with introducing this new approach, we proposed a dataset by identifying the most commonly used keywords in documents and using the most appropriate documents to help them with the abundance of vocabulary. Then, using the proposed approach, techniques of text categorization, evaluation criteria and ranking algorithms, the data were analyzed and examined. The evaluation results show that using the combination of features approach improves the quality and effects on efficient ranking.