Abstract:
Multimodal lifelog data consists of continual streams of multimodal sensor data about the life experience of an individual. In order to be effective, any lifelog retrieva...Show MoreMetadata
Abstract:
Multimodal lifelog data consists of continual streams of multimodal sensor data about the life experience of an individual. In order to be effective, any lifelog retrieval system needs to segment continual lifelog data into manageable units. In this paper, we explore the effect of incorporating manual annotations into the lifelog event segmentation process, and we present a study into the effect of high-quality manual annotations on a query-time document segmentation process for lifelog data and evaluate the approach using an open and available test collection. We show that activity based manual annotations enhance the understanding of information retrieval and we highlight a number of potential topics of interest for the community.
Published in: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)
Date of Conference: 11-15 March 2019
Date Added to IEEE Xplore: 06 June 2019
ISBN Information: