From Multimodal to Unimodal Webpages for Developing Countries
This addresses network connectivity issues in developing countries by converting multimodal webpages to unimodal ones, though it is an incremental application of existing methods.
The paper tackles webpage rendering delays in developing countries by proposing a Canonical Correlation Analysis (CCA) approach to replace high-cost images with low-cost text, reducing memory cost by at least 83.35%.
The multimodal web elements such as text and images are associated with inherent memory costs to store and transfer over the Internet. With the limited network connectivity in developing countries, webpage rendering gets delayed in the presence of high-memory demanding elements such as images (relative to text). To overcome this limitation, we propose a Canonical Correlation Analysis (CCA) based computational approach to replace high-cost modality with an equivalent low-cost modality. Our model learns a common subspace for low-cost and high-cost modalities that maximizes the correlation between their visual features. The obtained common subspace is used for determining the low-cost (text) element of a given high-cost (image) element for the replacement. We analyze the cost-saving performance of the proposed approach through an eye-tracking experiment conducted on real-world webpages. Our approach reduces the memory-cost by at least 83.35% by replacing images with text.