Extracting Knowledge from and for Meetings

Meetings are a fundamental part of a group decision-making process. As organizations grow across the globe and remote teams rise, the meetings become even more complex. Therefore, new technologies expanded the definition of a meeting as a face-to-face situation to an activity distributed in space and time. In this research, we identify similarities among meetings types and classify them using knowledge management principles. This information may be used to help with planning meetings, capturing information, reusing knowledge, and creating best practices tailored for each meeting type. We also develop a meeting transcription application, which interfaces with transcription software to extract information from meetings and index them for further use. This transcription strategy facilitates communication, bringing flexibility and efficiency by automatically transcribing meetings in a text while providing a more accurate and reliable method of meeting documentation. A use case is described using the solution, to exemplify its operation.