Considering manual annotations in dynamic segmentation of multimodal lifelog data
Gupta, Rashmi and Gurrin, CathalORCID: 0000-0003-2903-3968
(2019)
Considering manual annotations in dynamic segmentation of multimodal lifelog data.
In: ARDUOUS'19 - 3rd International Workshop on Annotation of useR Data for UbiquitOUs Systems, 11-15 Mar 2019, Kyoto, Japan.
ISBN 978-1-5386-9151
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.