Restaurant recommender system based on psychographic and demographic factors in mobile environment

R. Katarya, O. Verma
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引用次数: 15

Abstract

Today the number of smart phone users is approximately 1.6 billion and with drastic improvement in internet technology, the way information is accessed and used is changed completely. Recommendation systems filter and recommend only relevant data to the user using different filtering techniques. Restaurant recommendation is one of the latest research area which requires further effort. In this paper, a new model is introduced for the restaurant recommendation which uses first psychographic attributes where lifestyle, interest and personality of an individual can be predicted based on mobile usage pattern, second demographic attributes such as age, gender etc. and third current location. We have verified over results using standard statistical metrics like root mean square or variance.
移动环境下基于心理和人口因素的餐厅推荐系统
今天,智能手机用户的数量大约是16亿,随着互联网技术的急剧进步,信息的获取和使用方式完全改变了。推荐系统使用不同的过滤技术过滤并只向用户推荐相关的数据。餐厅推荐是一个最新的研究领域,需要进一步努力。本文介绍了一种新的餐厅推荐模型,该模型首先使用心理属性,其中个人的生活方式,兴趣和个性可以根据移动使用模式进行预测,其次是人口统计属性,如年龄,性别等,第三是当前位置。我们已经使用标准统计指标如均方根或方差验证了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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