  Online shopping has become a valuable modern convenience, but blind or low
vision (BLV) users still face significant challenges using it, because of: 1)
inadequate image descriptions and 2) the inability to filter large amounts of
information using screen readers. To address those challenges, we propose
Revamp, a system that leverages customer reviews for interactive information
retrieval. Revamp is a browser integration that supports review-based
question-answering interactions on a reconstructed product page. From our
interview, we identified four main aspects (color, logo, shape, and size) that
are vital for BLV users to understand the visual appearance of a product. Based
on the findings, we formulated syntactic rules to extract review snippets,
which were used to generate image descriptions and responses to users' queries.
Evaluations with eight BLV users showed that Revamp 1) provided useful
descriptive information for understanding product appearance and 2) helped the
participants locate key information efficiently.
