Extracting Intention from Web Queries– Application in eHealth Personalization

Abstract

Personalizing healthcare applications requires capturing patient specific information, including medical history, health status, and mental aspects such as behaviors, intentions, and attitudes. This paper presents a privacy-friendly system to deduce patient intentions that can be used to personalized eHealth applications. In the proposed approach patient intention is deduced from web query logs via query categorization techniques. The architecture assumes a user application which conceals the user’s queries from the central system, while only relevant intentions are disclosed. The paper presents a prototype implementation of the proposed architecture to extract intentions for personalizing empowerment services for the cardiorenal patient. Emphasis is placed on identifying intentions related to travel, diet and physical exercise, as these play an important role for the daily management of cardiorenal disease.