A Historical Context Analysis of Changes in Content Management Ideology

Digital content has grown continually over the past years, yet acceptance of a common definition of what is content management still generates debates in IS communities. This research will be a qualitative study using a combined approach of historical and context analysis of literary artifacts for drawing inferences to explore the evolutionary changes in content management ideology. Using a seven-step process, a specific structure is designed with a systematic approach to encounter the phenomena being researched and present the evidence of the results. Performing an analysis on the evolution of content management from a historical perspective will benefit researchers and practitioners with foundational knowledge about this progression and provide insights into understanding concepts and strategies within the content management community

Use of a Fast Information Extraction Method as a Decision Support Tool

Ad-hoc extraction of information from documents can ensure the transparency of decisions made by an organization. Different Information Extraction methods have been applied to extract information from various domains. Most widely known methods use manually annotated training documents that require high development time. The automated training methods are not scalable to large application domains. We have developed a semi-automated knowledge-engineering method for building the knowledge-base with minimal efforts. Because our method reduces manual processing of the training data, the development process is very fast. We have developed a prototype application to extract information from the project-reports of the American Recovery and Reinvestment Act (ARRA) of 2009. The fast development process of our system, its scalability to large application domains, and its high extraction effectiveness will help the transparency of management decisions by extracting and mining relevant information