Tell Me What Is Good About This Property: Leveraging Reviews For
  Segment-Personalized Image Collection Summarization
Monika Wysoczanska Moran Beladev Karen Lastmann Assaraf Fengjun Wang Ofri Kleinfeld Gil Amsalem Hadas Harush Boker
Image collection summarization techniques aim to present a compact
representation of an image gallery through a carefully selected subset of
images that captures its semantic content. When it comes to web content,
however, the ideal selection can vary based on the user's specific intentions
and preferences. This is particularly relevant at Booking.com, where presenting
properties and their visual summaries that align with users' expectations is
crucial. To address this challenge, we consider user intentions in the
summarization of property visuals by analyzing property reviews and extracting
the most significant aspects mentioned by users. By incorporating the insights
from reviews in our visual summaries, we enhance the summaries by presenting
the relevant content to a user. Moreover, we achieve it without the need for
costly annotations. Our experiments, including human perceptual studies,
demonstrate the superiority of our cross-modal approach, which we coin as
CrossSummarizer over the no-personalization and image-based clustering
baselines.