Design and Communication of City Brand Image Based on Big Data and Personalized Recommendation System

Author:

Lin Yan1ORCID,Hu Guofeng1ORCID

Affiliation:

1. School of Art and Design, Guangdong University of Science and Technology, Dongguan, Guangdong 523083, China

Abstract

In order to define the positioning of the urban brand image, design the urban brand image, integrate and optimize the communication channels, improve the public participation awareness, and enhance the core competitiveness of the city. In this paper, a personalized recommendation search engine based on big data identifies keywords input by urban users. And give more accurate results based on some relevant information that can be extracted. This paper analyzes how to make better use of big data for tourism destination brand image management, and the existing shortcomings, and puts forward relevant suggestions. The industries related to cultural creative design and tourism elements constitute an intertwined cultural and tourism industry chain, and data technology plays an important role in the cultural and tourism industry chain. Through the development of tourism, tourists will produce comprehensive and diversified consumption in the city. Based on the analysis of big data, it can provide strong decision support for the government and industry managers, and realize the image design and communication of the urban brand identification system. Through the big data platform, establish the brand management strategy, improve the communication content of the city’s brand image, and timely feedback the opinions and suggestions of tourists on the tourism destination, so as to adjust the communication strategy of the tourism image according to the feedback information of tourists. The results show that the big data personalized recommendation system can achieve ideal results in urban brand value and urban tourism related factors.

Publisher

Hindawi Limited

Subject

Analysis

Reference20 articles.

1. Design and implementation of big data algorithm library teaching experiment platform;Z. Liang;Experimental Technology and Management,2020

2. AI algorithms, price discrimination and collusion: a technological, economic and legal perspective

3. Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?

4. Design of big data personalized recommendation system based on SSM framework;W. Huifang;Information and Computer,2022

5. Application intelligent search and recommendation system based on speech recognition technology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3