  Mainstream knowledge management researchers generally agree that knowledge
extracted from unstructured data and semi-structured data have become
imperative for organizational strategic decision making. In this research, we
develop a framework that captures and analyses unstructured data using machine
learning techniques and integrates knowledge and insight gained from the data
into traditional knowledge management systems. Unlike most frameworks published
in the literature that focuses on a specific type of unstructured data, our
frameworks cut across the varieties of unstructured data ranging from textual
data from social network sites, online forums, discussion boards, reviews to
audio data, image data and video data. We highlight some pre-processing and
processing techniques for these data and also highlight some standard output.
We evaluate the framework by developing a textual data application programming
interface (API) using python and beautiful soup and we perform sentiment
analysis on the students review data collected through the API.
