Automatic analysis of textual hotel reviews

被引：41
作者：
García-Pablos A. [1 ]
Cuadros M. [2 ]
Linaza M.T. [1 ]
机构：
[1] Department of eTourism and Cultural Heritage, Vicomtech-IK4, San Sebastián
[2] Department of Human Speech and Language Technologies, Vicomtech-IK4, San Sebastián
来源：
Information Technology & Tourism | 2016年 / 16卷 / 1期
关键词：
Customer-generated reviews; Sentiment analysis; Text analysis;
D O I：
10.1007/s40558-015-0047-7
中图分类号：
学科分类号：
摘要：
Social Media and consumer-generated content continue to grow and impact the hospitality domain. Consumers write online reviews to indicate their level of satisfaction with a hotel and inform other consumers on the Internet of their hotel stay experience. A number of websites specialized in tourism and hospitality have flourished on the Web (e.g. Tripadvisor). The tremendous growth of these data-generating sources demands new tools to deal with them. To cope with big amounts of customer-generated reviews and comments, Natural Language Processing (NLP) tools have become necessary to automatically process and manage textual customer reviews (e.g. to perform Sentiment Analysis). This work describes OpeNER, a NLP platform applied to the hospitality domain to automatically process customer-generated textual content and obtain valuable information from it. The presented platform consists of a set of Open Source and free NLP tools to analyse text based on a modular architecture to ease its modification and extension. The training and evaluation has been performed using a set of manually annotated hotel reviews gathered from websites like Zoover and HolidayCheck. © 2015, Springer-Verlag Berlin Heidelberg.
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收藏
页码：45 / 69
页数：24
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