Enhancing Hotel Recommendations with AI: LLM-Based Review Summarization and Query-Driven Insights
Nikolaos Belibasakis, Anastasios Giannaros, Ioanna Giannoukou, Spyros Sioutas

TL;DR
This paper presents instaGuide, a web application that uses Large Language Models to summarize and extract insights from user reviews on booking platforms, significantly improving the efficiency of choosing short rental apartments.
Contribution
The paper introduces a novel LLM-based tool that automates review summarization and query-driven insights for property selection on booking platforms.
Findings
LLMs effectively summarize lengthy reviews.
Review summarization reduces user search time.
Enhanced decision-making in property selection.
Abstract
The increasing number of data a booking platform such as Booking.com and AirBnB offers make it challenging for interested parties to browse through the available accommodations and analyze reviews in an efficient way. Efforts have been made from the booking platform providers to utilize recommender systems in an effort to enable the user to filter the results by factors such as stars, amenities, cost but most valuable insights can be provided by the unstructured text-based reviews. Going through these reviews one-by-one requires a substantial amount of time to be devoted while a respectable percentage of the reviews won't provide to the user what they are actually looking for. This research publication explores how Large Language Models (LLMs) can enhance short rental apartments recommendations by summarizing and mining key insights from user reviews. The web application presented in…
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Taxonomy
TopicsAI in Service Interactions · Recommender Systems and Techniques · Digital Marketing and Social Media
