Prospective memory aid: A reminding model based on Fuzzy Cognitive Maps

Prospective memory (PM) failure, which is the failure to recall future events or intentions, can lead to serious consequences. Although many PM aid systems have been developed, there are three critical challenges which are yet to be addressed by any existing systems: (1) determining appropriate number of reminders, (2) arranging effective reminder schedule and (3) selecting appropriate reminding method based on context. We propose a new reminding model to address these three challenges. The model draws its theoretical basis from existing PM research and employs Fuzzy Cognitive Maps to incorporate the theoretical basis computationally. Specifically, poring over extensive PM literature, a number of factors and contextual elements are identified, which can help determining the number of reminders and selecting appropriate reminding method. The proposed model captures the complex and dynamic relationships among the factors and elements computationally. To evaluate the proposed reminding model, it was incorporated into a mobile app, ReminderPM. A field study was carried out to evaluate it. Study results support that ReminderPM can provide a better overall experience and remind more effectively.