CSR: Small: Efficient and Scalable Systems Support for Mobile Group Formation, Inference, Recommendation and Classification

智能手机的用户越来越多地使用他们的移动的设备来组织活动，作为朋友、家人和同事的移动的群组。 为了提高这种移动的群体内的互动的丰富性，本研究项目调查创建新的移动的群体服务和开发一个实用的框架，这将使这种新的功能，如提供建议，以移动的群体的人与不同的利益。 该项目提出开发新的方法来识别何时在移动的社交网络中发生了一组用户的网络欺凌。 此外，由于每天有数百万组用户使用社交媒体进行交流，本项目将研究如何扩展移动的用户组的推荐和识别算法，以便快速为此类用户组提供准确的推荐，并快速识别移动的群体网络欺凌行为。该项目的研究及其智力价值集中在推进理解移动的群体动态的最新技术水平，为移动的用户群体创建准确的推荐和分类算法，并开发可扩展的基础设施，在此基础上可以部署新的移动的群体应用程序。 研究计划是由两个新颖的和有代表性的案例研究，即移动的群体推荐和网络欺凌检测在移动的群体。该项目将产生一个综合系统框架，由六个主要组成部分组成，以支持移动的群体应用程序：移动的客户端应用程序;一套核心移动的群体服务，包括投票、多播通信、评级和角色定义;一套移动的群体信息;一个移动的群体推理引擎;一个移动的群体推荐和预测引擎;以及一个移动的群体分类引擎。 社会作为一个整体可能会大大受益于新的移动的组服务和算法的移动的组推荐和分类内开发的这个项目，从而使移动的用户组更容易和丰富的互动。 此外，研究界将受益于开放源码基础设施的创建，可以刺激对移动的用户群体的进一步研究。 该项目将为初中/高中学生制作STEM教育材料，招募本科生和代表性不足的妇女和少数民族进行研究，将研究结果纳入调查人员教授的课程，并加强跨学科研究。

Users of smartphones are increasingly using their mobile devices to organize activities as mobile groups of friends, family, and colleagues. In order to improve the richness of interaction within such mobile groups, this research project investigates the creation of new mobile group services and the development of a practical framework that will enable such novel capabilities as providing recommendations to mobile groups of people with diverse interests. This project proposes to develop novel ways to identify when cyberbullying by a group of users is occurring in mobile social networks. In addition, since there are millions of groups of users who use social media every day to communicate, this project will investigate how recommendation and identification algorithms for mobile groups of users can be made to scale so they can quickly provide accurate recommendations to such groups of users, and rapidly identify mobile group cyberbullying behavior. This project's research and its intellectual merit focuses on advancing the state of the art in understanding mobile group dynamics, creating accurate recommendation and classification algorithms for mobile groups of users, and developing scalable infrastructure upon which new mobile group applications can be deployed. The research plan is driven by two novel and representative case studies, namely mobile group recommendation and cyberbullying detection in mobile groups. The project will generate an integrated systems framework consisting of six major components to support mobile group applications: mobile client apps; a set of core mobile group services including voting, multicast communication, rating, and role definition; a collection of mobile group information; a mobile group inference engine; a mobile group recommendation and prediction engine; and a mobile group classification engine. Society as a whole may strongly benefit from new mobile group services and algorithms for mobile group recommendation and classification developed within this project, thereby enabling mobile groups of users to more easily and richly interact. Further, the research community will benefit by the creation of open source infrastructure that can stimulate further research on mobile groups of users. The project will produce STEM educational materials for middle/high school students, recruit undergraduates and underrepresented women and minorities for research, integrate the results of the research into classes taught by the investigators, and strengthen interdisciplinary research.