A novel approach to personalize the healthcare video search

Abstract

Due to the increasing growth of the web, these days Internet is broadly utilized by users to fulfill different data needs. Sometimes, more precise information related to specific streams such as Healthcare is not available on the internet that satisfies the user's information need. There is a specific category of users such as doctors who really interested in the videos related to disease diagnosis and its treatment. Sometimes, doctors are not able to find the root cause of disease, so they are interested in the previous treatment given to that patient or similar disease patients in order to give better disease treatment. So making such videos available through a specific video search engine is very important, as these videos are useful to handle the very critical situations while diagnosis and treatment. The proposed system intends to show the most relevant videos for a specific users query with the help of video search engine for healthcare data. Healthcare data is easily available or can be recorded at low cost. The proposed method is used to show various relevant videos for a given user's need by keyword based label matching. The proposed method performs video data collection and speech to text conversion to create the transcription snippets. Finally, keyword based labeling is done with the help of that transcription snippets and prescription reports in order to show more precise and relevant video search results for a given users query. Then these keywords can be used to rearrange the video search outputs. This proposed system is very effective for disease prescription analysis as well as it helps practitioners who are new.