SAS模块：Text Mining with SAS® Text Miner 发表评论(0) 编辑词条

Overview：SAS Text Miner provides a rich suite of tools for discovering and extracting knowledge from text documents. It transforms textual data into a usable, intelligible format that facilitates classifying documents, finding explicit relationships or associations between documents, and clustering documents into categories. It's the first mining solution that tightly integrates text-based information with structured data for improved analyses and decision making.

简介：SAS文本挖掘为发现和从文本文件中提取知识提供了丰富的工具套件。它会将文件的文本数据进行分类，寻找明确的文档之间的关系或协会，和集群文件，进行分类转换成一个实用，便于理解的格式。基于文本的改进分析和决策的结构化数据信息，这是第一次挖掘紧密集成的解决方案。

Benefits
1、Save money and resources. There are many tasks that are currently performed manually or completely ignored. With SAS Text Miner, organizational activities are streamlined, resulting in immediate ROI and performance gain.
2、Recognize trends and spot business opportunities. Analysis of information such as blogs, customer feedback and call center notes may provide valuable information about your customers’ critical issues, insights into service and product needs. This helps decision makers gain meaningful insights that successfully drive overall business direction.
3、Process a variety of information sources, including text and traditional databases, to deliver complete views of an organization. Combining structured data and unstructured data types enables you to automate many of the manual steps required before analysis traditionally begins.

优点
1、节省资金和资源。有很多任务常常人工完成或完全被忽略掉。用SAS挖掘，可以使活动组织精简，使投资回报率和性能提高。
2、发掘商业趋势和商业机会。分析例如博客，客户反馈和呼叫中心记录的资料可以提供有关客户的关键问题的有价值的信息，帮助企业看到服务和产品的需求。这有助于决策者获得有意义的见解，成功地推动整体业务发展方向。
3、过程的信息来源，包括文本和各种传统的数据库，提供一个组织完整的看法。结合结构化数据和非结构化数据类型，您可以在自动化分析所需的许多传统的手动步骤开始。

Features
1、Universal data access     2、Support for multiple languages     3、Self-documenting interface

4、Comprehensive text preprocessing capabilities        5、Extensive feature extraction    6、Dimension reduction techniques

7、Text clustering algorithms   8、Interactive training   9、Document categorization

特点：

1，通用数据访问
2，多语言支持
3，自我记录界面
4，综合文本预处理功能
5，广泛的特征提取
6，微小消除技术
7，文本聚类算法
8，互动式培训
9，文档分类