%0 Conference Proceedings
%T A Sentiment-Based Hotel Review Summarization Using Machine Learning Techniques
%+ Department of Computer Engineering and Informatics [Patras]
%A Bompotas, Agorakis
%A Ilias, Aristidis
%A Kanavos, Andreas
%A Makris, Christos
%A Rompolas, Gerasimos
%A Savvopoulos, Alkiviadis
%Z Part 2: 9th Mining Humanistic Data Workshop
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 16th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI)
%C Neos Marmaras, Greece
%Y Ilias Maglogiannis
%Y Lazaros Iliadis
%Y Elias Pimenidis
%I Springer International Publishing
%3 Artificial Intelligence Applications and Innovations. AIAI 2020 IFIP WG 12.5 International Workshops
%V AICT-585
%P 155-164
%8 2020-06-05
%D 2020
%R 10.1007/978-3-030-49190-1_14
%K Classification
%K Machine learning
%K Neural networks
%K Opinion mining
%K Sentiment analysis
%Z Computer Science [cs]Conference papers
%X With the advent of social media, there is a data abundance so that analytics can be reliably designed for ultimately providing valuable information towards a given product or service. In this paper, we examine the problem of classifying hotel critiques using views expressed in users’ reviews. There is a massive development of opinions and reviews on the web, which invariably include assessments of products and services, and beliefs about events and persons. In this study, we aim to face the problem of the forever increasing amount of opinionated data that is published in a variety of data sources. The intuition is the extraction of meaningful services despite the lack of sufficient existing architectures. Another important aspect that needs to be taken into consideration when dealing with brand monitoring, relates to the rapid heterogeneous data processing, which is vital to be implemented in real-time in order for the business to react in a more immediate way.
%G English
%Z TC 12
%Z WG 12.5
%2 https://inria.hal.science/hal-03677621/document
%2 https://inria.hal.science/hal-03677621/file/500088_1_En_14_Chapter.pdf
%L hal-03677621
%U https://inria.hal.science/hal-03677621
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-585