An Unstructured Information Management Architecture Approach to Text Analytics of Cancer Blogs

In this research the authors explore the potential of the Unstructured Information Management Architecture (UIMA) platform in text analytics of cancer blogs. The application is developed using the UIMA open source platform. They use the text analytics methods of categorization, clustering, taxonomic classification, and others to identify and analyze the patterns in cancer blog postings. The authors establish a comprehensive UIMA methodology for developing text analytics applications for the analysis of cancer blogs. Additional insights are extracted through the development of categories or keywords contained in the blogs, the development of a taxonomy and the examination of relationships among the categories. The application has the potential for generalizability and implementation with health content in other blogs and social media. It has the potential to provide insight and decision support for cancer management and to facilitate the efficient and relevant search for information on cancer.

An Unstructured Information Management Architecture Approach to Text Analytics of Cancer Blogs

In this research the authors explore the potential of the Unstructured Information Management Architecture (UIMA) platform in text analytics of cancer blogs. The application is developed using the UIMA open source platform. They use the text analytics methods of categorization, clustering, taxonomic classification, and others to identify and analyze the patterns in cancer blog postings. The authors establish a comprehensive UIMA methodology for developing text analytics applications for the analysis of cancer blogs. Additional insights are extracted through the development of categories or keywords contained in the blogs, the development of a taxonomy and the examination of relationships among the categories. The application has the potential for generalizability and implementation with health content in other blogs and social media. It has the potential to provide insight and decision support for cancer management and to facilitate the efficient and relevant search for information on cancer.

Classify the Search Result Based on IBM OminiFind Edition and UIMA

A method is proposed which uses the IBM OmniFind Enterprise Edition combined with IBM open source of unstructured information management architecture of Unstructured Information Management Architecture (UIMA), to realize the IBM OmniFind Enterprise Edition semantic search engine search and result classification. This method makes the search space and function more widely, which can not only meet the higher demand of the part of the user, but also increase the competitiveness of the client application.