Event-Based Social Networking System With Recommendation Engine
Author:
Affiliation:
1. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
2. College of Engineering Guindy, Anna University, India
Abstract
For over a decade, social networking has been ruling over the internet and plays a vital role in day-to-day life. However, for a new network to survive in this market, exclusivity is a necessity. As a result, the goal of this work is to create a network for hosting and managing volunteering and events. Furthermore, the network will feature a recommendation system to provide users with events based on their interests and preferences according to how they interact with the platform. The proposed system is exclusively meant for event post creation and management and also it focuses on event posts with interactions such as replies, likes, interest, and disinterest options. This system has been implemented and deployed with the title ‘Evento' with the recommendation engine boasting an average purity index of 0.8031 for approximately 30 users. The results for recommendations have been chosen considering purity index and fisher optimization criterion metrics. Based on the experimental results, the proposed social network system with the recommendation engine has been found to be sufficient.
Publisher
IGI Global
Subject
Decision Sciences (miscellaneous),Information Systems
Reference19 articles.
1. Tourism recommendation system based on semantic clustering and sentiment analysis
2. Social Media Recommender Systems: Review and Open Research Issues
3. An intelligent recommender system using social trust path for recommendations in web-based social networks
4. Ben-Shimon, D., Tsikinovsky, A., Rokach, L., Meisles, A., Shani, G., & Naamani, L. (2007). Recommender system from personal social networks. In Advances in Intelligent Web Mastering:Proceedings of the 5th Atlantic Web Intelligence Conference–AWIC’2007,Fontainbleau, France,June 25–27, 2007 (pp. 47-55). Springer Berlin Heidelberg.
5. A topic sentiment based method for friend recommendation in online social networks via matrix factorization
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