On the Selection of Anchors and Targets for Video Hyperlinking
release_p3pcrvqk3fbunek4j5uq7cu2hi
by
Zhi-Qi Cheng, Hao Zhang, Xiao Wu, Chong-Wah Ngo
2018
Abstract
A problem not well understood in video hyperlinking is what qualifies a
fragment as an anchor or target. Ideally, anchors provide good starting points
for navigation, and targets supplement anchors with additional details while
not distracting users with irrelevant, false and redundant information. The
problem is not trivial for intertwining relationship between data
characteristics and user expectation. Imagine that in a large dataset, there
are clusters of fragments spreading over the feature space. The nature of each
cluster can be described by its size (implying popularity) and structure
(implying complexity). A principle way of hyperlinking can be carried out by
picking centers of clusters as anchors and from there reach out to targets
within or outside of clusters with consideration of neighborhood complexity.
The question is which fragments should be selected either as anchors or
targets, in one way to reflect the rich content of a dataset, and meanwhile to
minimize the risk of frustrating user experience. This paper provides some
insights to this question from the perspective of hubness and local intrinsic
dimensionality, which are two statistical properties in assessing the
popularity and complexity of data space. Based these properties, two novel
algorithms are proposed for low-risk automatic selection of anchors and
targets.
In text/plain
format
Archived Files and Locations
application/pdf 383.1 kB
file_o6oilhrrp5g7pc6o5onees2alu
|
arxiv.org (repository) web.archive.org (webarchive) |
1804.05286v1
access all versions, variants, and formats of this works (eg, pre-prints)