告诉我这处房产好在哪里：利用评论进行分众个性化的图像集摘要生成
Tell Me What Is Good About This Property: Leveraging Reviews For Segment-Personalized Image Collection Summarization
AI总结：
本文提出CrossSummarizer，利用房产评论提取用户关注点，在无需标注的情况下生成符合用户意图的个性化图像集摘要，实验证明其优于无个性化和图像聚类基线。
摘要：
图像集摘要技术旨在通过精心挑选的图像子集来呈现图像库的紧凑表示，以捕捉其语义内容。然而，对于网络内容而言，理想的选择可能因用户的具体意图和偏好而异。这在Booking.com上尤为相关，因为呈现符合用户期望的房产及其视觉摘要至关重要。为应对这一挑战，我们在房产视觉摘要中考虑用户意图，通过分析房产评论并提取用户提到的最重要方面。通过将评论中的见解融入视觉摘要，我们通过向用户呈现相关内容来增强摘要效果。此外，我们在无需昂贵标注的情况下实现了这一目标。我们的实验（包括人类感知研究）证明了我们所提出的跨模态方法——我们称之为CrossSummarizer——相对于无个性化基线和基于图像的聚类基线的优越性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
