Text Mining for Personalized Knowledge Extraction From Online Support Groups

Abstract

The traditional approach to health care is being revolutionized by the rapid adoption of patient-centered healthcare models. The successful transformation of patients from passive recipients to active participants is largely attributed to increased access to healthcare information. Online support groups present a platform to seek and exchange information in an inclusive environment. As the volume of text on online support groups continues to grow exponentially, it is imperative to improve the quality of retrieved information in terms of relevance, reliability, and usefulness. We present a text-mining approach that generates a knowledge extraction layer to address this void in personalized in..